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, Available online
, Manuscript accepted 25 September 2023, doi: 10.1007/s00376-023-3106-6
Abstract:
Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes, yet its parameterization in numerical models remains a great challenge, partly due to the lack of high-resolution observations. This study describes the large eddy simulation (LES) dataset for four shallow convection cases that differ primarily in inversion strength, which can be used as a surrogate for real data. To reduce the uncertainty in LES modeling, three different large eddy models were used, including System for Atmospheric Modeling (SAM), Weather Research and Forecasting model (WRF), and UCLA-LES. Results show that different models generally exhibit similar behavior for each of the shallow convection case, despite some differences in details of the convective structure. In addition to grid-averaged fields, conditionally sampled variables such as in-cloud moisture and vertical velocity are also provided, which are indispensable for the calculation of entrainment/detrainment rate. Considering the essentiality of entraining/detraining process in the parameterization of cumulus convection, the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.
Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes, yet its parameterization in numerical models remains a great challenge, partly due to the lack of high-resolution observations. This study describes the large eddy simulation (LES) dataset for four shallow convection cases that differ primarily in inversion strength, which can be used as a surrogate for real data. To reduce the uncertainty in LES modeling, three different large eddy models were used, including System for Atmospheric Modeling (SAM), Weather Research and Forecasting model (WRF), and UCLA-LES. Results show that different models generally exhibit similar behavior for each of the shallow convection case, despite some differences in details of the convective structure. In addition to grid-averaged fields, conditionally sampled variables such as in-cloud moisture and vertical velocity are also provided, which are indispensable for the calculation of entrainment/detrainment rate. Considering the essentiality of entraining/detraining process in the parameterization of cumulus convection, the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.
, Available online
, Manuscript accepted 25 September 2023, doi: 10.1007/s00376-023-3034-5
Abstract:
Based on the hourly rain gauge data during May-September of 2016-2020, we analyze the spatio-temporal distributions of total rainfall (TR) and short-duration heavy rainfall (SDHR, hourly rainfall ≥ 20 mm) and their diurnal variations over the middle reaches of the Yangtze River basin. For all three types of terrains (i.e., mountain, foothill and plain), the amount of TR and SDHR both maximized in June/July, and the contribution of SDHR to TR (CST) peaked in August (amount: 23%; frequency: 1.74%). Foothill rainfall is characterized by a high TR amount and a high CST (in amount); mountain rainfall is characterized by a high TR frequency but a small CST (in amount); and plain rainfall shows a low TR amount and frequency, but a high CST (in amount). Overall, stations with high TR (amount and frequency) are mainly located in the mountains and foothills, while those with high SDHR (amount and frequency) are mainly concentrated in the foothills and plains close to mountainous areas. For all three types of terrains, diurnal variations of both TR and SDHR exhibit a double-peak (weak early morning and strong late afternoon) and a phase shift from the early-morning peak to the late-afternoon peak from May to August. Around the late afternoon peak, the amount and frequency of the SDHR in the foothills is larger than those of mountains and plains. The TR amount in the foothills increase significantly from midnight to afternoon, suggesting that thermal instability may play an important role in this process.
Based on the hourly rain gauge data during May-September of 2016-2020, we analyze the spatio-temporal distributions of total rainfall (TR) and short-duration heavy rainfall (SDHR, hourly rainfall ≥ 20 mm) and their diurnal variations over the middle reaches of the Yangtze River basin. For all three types of terrains (i.e., mountain, foothill and plain), the amount of TR and SDHR both maximized in June/July, and the contribution of SDHR to TR (CST) peaked in August (amount: 23%; frequency: 1.74%). Foothill rainfall is characterized by a high TR amount and a high CST (in amount); mountain rainfall is characterized by a high TR frequency but a small CST (in amount); and plain rainfall shows a low TR amount and frequency, but a high CST (in amount). Overall, stations with high TR (amount and frequency) are mainly located in the mountains and foothills, while those with high SDHR (amount and frequency) are mainly concentrated in the foothills and plains close to mountainous areas. For all three types of terrains, diurnal variations of both TR and SDHR exhibit a double-peak (weak early morning and strong late afternoon) and a phase shift from the early-morning peak to the late-afternoon peak from May to August. Around the late afternoon peak, the amount and frequency of the SDHR in the foothills is larger than those of mountains and plains. The TR amount in the foothills increase significantly from midnight to afternoon, suggesting that thermal instability may play an important role in this process.
, Available online
, Manuscript accepted 25 September 2023, doi: 10.1007/s00376-023-3100-z
Abstract:
Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling. This study emphasized the influence of initial soil temperature (ST) and soil moisture (SM) conditions on land surface energy and water simulation in the permafrost region on the Tibetan Plateau (TP) in Community Land Model version 5.0 (CLM5.0). The results indicate the default initial schemes for ST and SM in CLM5.0 were simplistic and inaccuracy represent the soil characteristic of permafrost on the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site. Applying the long-term spin-up method to obtain initial soil conditions only led to limited improvement in simulating soil hydrothermal and surface energy fluxes. The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost, which coexistence of soil liquid water (SLW) with soil ice (SI), and ST below freezing temperature, effectively enhancing the accuracy of soil hydrothermal and surface energy fluxes simulation. The improvement of modified initial soil schemes greatly exceeded that achieved through the long-term spin-up method. Three modified initial soil schemes experiments resulted in a 64%, 88%, and 77% reduction in the average mean bias error (MBE) of ST, and a 13%, 21%, and 19% reduction in the average root mean square error (RMSE) of SLW compared to default simulation results. Also, the average MBE of net radiation was reduced by 7%, 22%, and 21%.
Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling. This study emphasized the influence of initial soil temperature (ST) and soil moisture (SM) conditions on land surface energy and water simulation in the permafrost region on the Tibetan Plateau (TP) in Community Land Model version 5.0 (CLM5.0). The results indicate the default initial schemes for ST and SM in CLM5.0 were simplistic and inaccuracy represent the soil characteristic of permafrost on the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site. Applying the long-term spin-up method to obtain initial soil conditions only led to limited improvement in simulating soil hydrothermal and surface energy fluxes. The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost, which coexistence of soil liquid water (SLW) with soil ice (SI), and ST below freezing temperature, effectively enhancing the accuracy of soil hydrothermal and surface energy fluxes simulation. The improvement of modified initial soil schemes greatly exceeded that achieved through the long-term spin-up method. Three modified initial soil schemes experiments resulted in a 64%, 88%, and 77% reduction in the average mean bias error (MBE) of ST, and a 13%, 21%, and 19% reduction in the average root mean square error (RMSE) of SLW compared to default simulation results. Also, the average MBE of net radiation was reduced by 7%, 22%, and 21%.
, Available online
, Manuscript accepted 12 September 2023, doi: 10.1007/s00376-023-3073-y
Abstract:
Recent studies on tropical cyclone (TC) intensity change indicate that the development of a vertically aligned TC circulation is a key feature to the rapid intensification (RI) while understanding how the vortex alignment occurs is a challenging topic in the TC intensity change research. Based on the simulation outputs of North Atlantic Hurricane Wilma (2005) and western North Pacific Typhoon Rammasun (2014), vortex track oscillations at different vertical levels and the associated role in the vortex alignment are examined to improve our understanding of the vortex alignment during the RI of TCs initially with hurricane intensity. It is found that vortex tracks at different vertical levels oscillate consistently in speed and direction during the RI of the two simulated TCs. While the consistent track oscillation reduces the tilt oscillation during the RI, the reduction of vortex tilt results mainly from the mean track before the RI. It is also found that the vortex tilt is primarily due to the mean vortex track before and after the RI. The track oscillations are closely associated with wavenumber-1 vortex Rossby waves that are dominant wavenumber-1 circulations in the TC inner-core region. This study suggests that the dynamics of the wavenumber-1 vortex Rossby waves play an important role in the regulation of the physical processes associated with the track oscillation and vertical alignment of TCs.
Recent studies on tropical cyclone (TC) intensity change indicate that the development of a vertically aligned TC circulation is a key feature to the rapid intensification (RI) while understanding how the vortex alignment occurs is a challenging topic in the TC intensity change research. Based on the simulation outputs of North Atlantic Hurricane Wilma (2005) and western North Pacific Typhoon Rammasun (2014), vortex track oscillations at different vertical levels and the associated role in the vortex alignment are examined to improve our understanding of the vortex alignment during the RI of TCs initially with hurricane intensity. It is found that vortex tracks at different vertical levels oscillate consistently in speed and direction during the RI of the two simulated TCs. While the consistent track oscillation reduces the tilt oscillation during the RI, the reduction of vortex tilt results mainly from the mean track before the RI. It is also found that the vortex tilt is primarily due to the mean vortex track before and after the RI. The track oscillations are closely associated with wavenumber-1 vortex Rossby waves that are dominant wavenumber-1 circulations in the TC inner-core region. This study suggests that the dynamics of the wavenumber-1 vortex Rossby waves play an important role in the regulation of the physical processes associated with the track oscillation and vertical alignment of TCs.
, Available online
, Manuscript accepted 12 September 2023, doi: 10.1007/s00376-023-3032-7
Abstract:
This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature (SST). The associated precipitation in the mock-Walker cells exhibits three different modes, including a single peak of precipitation over the SST maximum (mode 1), symmetric double peaks of precipitation straddling the SST maximum (mode 2), and a single peak of precipitation on one side of the SST maximum (mode 3). The three modes are caused by three distinct convective activity center migration traits. Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes. When the SST gradient is large, the virtual effect may be strong enough to overcome the temperature effect, generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center. The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.
This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature (SST). The associated precipitation in the mock-Walker cells exhibits three different modes, including a single peak of precipitation over the SST maximum (mode 1), symmetric double peaks of precipitation straddling the SST maximum (mode 2), and a single peak of precipitation on one side of the SST maximum (mode 3). The three modes are caused by three distinct convective activity center migration traits. Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes. When the SST gradient is large, the virtual effect may be strong enough to overcome the temperature effect, generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center. The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.
, Available online
, Manuscript accepted 04 September 2023, doi: 10.1007/s00376-023-2382-5
Abstract:
Cloud top pressure (CTP) is one of the critical cloud properties that significantly affects the cloud radiation effect. Multi-angle polarized sensors can employ polarized bands (490 nm) or O2 A-bands (763 and 765 nm) to retrieve the CTP. However, the CTP retrieved by the two methods shows inconsistent results in certain cases, and large uncertainties in low and thin cloud retrievals, which may lead to challenges in subsequent applications. This study proposes a synergistic algorithm that considers both O2 A-bands and polarized bands using a random forest (RF) model. LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model of CTP. Additionally, through analysis, we proposed that the polarized signal becomes saturated as the cloud optical thickness (COT) increases, necessitating a particular treatment for COT < 10 to improve the algorithm's stability. The synergistic method was then applied to the directional polarized camera (DPC) and Polarized and Directionality of the Earth’s Reflectance (POLDER) measurements for evaluation, and the resulting retrieval accuracy of the POLDER-based measurements (RMSE=121.431 hPa, R2=0.827 and RMSE=30.611 hPa, R=0.470, respectively) were higher than that of the MODIS and POLDER Rayleigh pressure measurements. The synergistic algorithm also showed good performance in the application of DPC data. This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm in the Cloud Application for Remote Sensing, Atmospheric Radiation, and Updating Energy (CARE) platform.
Cloud top pressure (CTP) is one of the critical cloud properties that significantly affects the cloud radiation effect. Multi-angle polarized sensors can employ polarized bands (490 nm) or O2 A-bands (763 and 765 nm) to retrieve the CTP. However, the CTP retrieved by the two methods shows inconsistent results in certain cases, and large uncertainties in low and thin cloud retrievals, which may lead to challenges in subsequent applications. This study proposes a synergistic algorithm that considers both O2 A-bands and polarized bands using a random forest (RF) model. LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model of CTP. Additionally, through analysis, we proposed that the polarized signal becomes saturated as the cloud optical thickness (COT) increases, necessitating a particular treatment for COT < 10 to improve the algorithm's stability. The synergistic method was then applied to the directional polarized camera (DPC) and Polarized and Directionality of the Earth’s Reflectance (POLDER) measurements for evaluation, and the resulting retrieval accuracy of the POLDER-based measurements (RMSE=121.431 hPa, R2=0.827 and RMSE=30.611 hPa, R=0.470, respectively) were higher than that of the MODIS and POLDER Rayleigh pressure measurements. The synergistic algorithm also showed good performance in the application of DPC data. This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm in the Cloud Application for Remote Sensing, Atmospheric Radiation, and Updating Energy (CARE) platform.
, Available online
, Manuscript accepted 25 August 2023, doi: 10.1007/s00376-023-3077-7
Abstract:
Little is known about the mechanism of climate–vegetation coverage coupling changes in the Tibetan Plateau (TP), the most climatically-sensitive and ecologically-fragile region with the highest terrain in the world. This study, using multi-source datasets (including satellite data and meteorological observations and reanalysis data) revealed the mutual feedback mechanisms between changes in climates (temperature and precipitation) and vegetation coverage in recent decades in the Hengduan Mountains Area (HMA) of the southeastern TP and their influences on climates in the downstream region, the Sichuan Basin (SCB). There is mutual facilitation between air temperature rising and vegetation coverage increasing in the HMA, which is most significant during winter, and then during spring, but insignificant during summer and autumn. Temperature rising significantly enhanced local vegetation coverage, and vegetation greening in turn heated the atmosphere via enhancing net heat flux from the surface to the atmosphere. The atmospheric heating anomaly over the HMA thickened the atmospheric column and increased upper-air pressure. The high-pressure anomaly dispersed downstream via the westerly, expanded across the SCB, and eventually increased the SCB temperature. This effect lasted from winter to the following spring, which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring. These results are helpful for estimating future variation trends in climate and eco-environmental in the HMA and SCB under warming scenarios and seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.
Little is known about the mechanism of climate–vegetation coverage coupling changes in the Tibetan Plateau (TP), the most climatically-sensitive and ecologically-fragile region with the highest terrain in the world. This study, using multi-source datasets (including satellite data and meteorological observations and reanalysis data) revealed the mutual feedback mechanisms between changes in climates (temperature and precipitation) and vegetation coverage in recent decades in the Hengduan Mountains Area (HMA) of the southeastern TP and their influences on climates in the downstream region, the Sichuan Basin (SCB). There is mutual facilitation between air temperature rising and vegetation coverage increasing in the HMA, which is most significant during winter, and then during spring, but insignificant during summer and autumn. Temperature rising significantly enhanced local vegetation coverage, and vegetation greening in turn heated the atmosphere via enhancing net heat flux from the surface to the atmosphere. The atmospheric heating anomaly over the HMA thickened the atmospheric column and increased upper-air pressure. The high-pressure anomaly dispersed downstream via the westerly, expanded across the SCB, and eventually increased the SCB temperature. This effect lasted from winter to the following spring, which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring. These results are helpful for estimating future variation trends in climate and eco-environmental in the HMA and SCB under warming scenarios and seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.
, Available online
, Manuscript accepted 23 August 2023, doi: 10.1007/s00376-023-3024-7
Abstract:
The East Asian trough (EAT) profoundly influences the East Asian spring climate. In this study, the relationship of the EATs among the three spring months is first investigated. Correlation analysis shows that the variability in March EAT is closely related to that of April EAT. The extended empirical orthogonal function (EEOF) analysis also confirms the co-variability of the March and April EATs. The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April. Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature (SST) pattern over the North Atlantic and SST anomaly over the tropical Indian Ocean. The dipole SST pattern over the North Atlantic, with one center east of Newfoundland Island and another east of Bermuda, could trigger a Rossby wave train to influence the EAT in March-April. The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence atmospheric circulation over the tropical western Pacific, subsequently impacting the southern part of the EAT in March-April. Besides the SST factors, the Northeast Asian snow cover could change the regional thermal condition and lead to persistence in the EAT anomalies from March to April. The three impact factors are generally independent of each other, jointly explaining large variations in the EAT EEOF1. Moreover, the signals of the three factors could be traced back to February, consequently providing a prediction source for the EAT variation in March and April.
The East Asian trough (EAT) profoundly influences the East Asian spring climate. In this study, the relationship of the EATs among the three spring months is first investigated. Correlation analysis shows that the variability in March EAT is closely related to that of April EAT. The extended empirical orthogonal function (EEOF) analysis also confirms the co-variability of the March and April EATs. The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April. Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature (SST) pattern over the North Atlantic and SST anomaly over the tropical Indian Ocean. The dipole SST pattern over the North Atlantic, with one center east of Newfoundland Island and another east of Bermuda, could trigger a Rossby wave train to influence the EAT in March-April. The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence atmospheric circulation over the tropical western Pacific, subsequently impacting the southern part of the EAT in March-April. Besides the SST factors, the Northeast Asian snow cover could change the regional thermal condition and lead to persistence in the EAT anomalies from March to April. The three impact factors are generally independent of each other, jointly explaining large variations in the EAT EEOF1. Moreover, the signals of the three factors could be traced back to February, consequently providing a prediction source for the EAT variation in March and April.
, Available online
, Manuscript accepted 15 August 2023, doi: 10.1007/s00376-023-3040-7
Abstract:
This paper investigates the homogeneity of the United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data of seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data showed that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the rest of the best track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades than the later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset was also evaluated and was found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.
This paper investigates the homogeneity of the United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data of seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data showed that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the rest of the best track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades than the later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset was also evaluated and was found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.
, Available online
, Manuscript accepted 27 July 2023, doi: 10.1007/s00376-023-2353-x
Abstract:
Assessment of past-climate simulations of regional climate models (RCMs) is important for understanding the reliability of RCMs when used to project future regional climate. Here we assess the performance and discuss possible causes of biases of a WRF-based RCM with a grid spacing of 50 km, named WRFG, from the North American Regional Climate Change Assessment Program (NARCCAP) in simulating the wet season precipitation over the central United States for a period when observational data are available. The RCM reproduces key features of precipitation distribution characteristics during late spring to early summer, although it tends to underestimate the magnitude of precipitation. This dry bias is partly due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagation of convective systems in simulation. Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor. The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds inbetween, leading to less warm moist air transport from the Gulf to the central Great Plains. The simulated low-level horizontal convergence fields are less favorable than reanalysis data for upward motion and hence for convection development also. Therefore, careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project change of precipitation in future climate scenarios.
Assessment of past-climate simulations of regional climate models (RCMs) is important for understanding the reliability of RCMs when used to project future regional climate. Here we assess the performance and discuss possible causes of biases of a WRF-based RCM with a grid spacing of 50 km, named WRFG, from the North American Regional Climate Change Assessment Program (NARCCAP) in simulating the wet season precipitation over the central United States for a period when observational data are available. The RCM reproduces key features of precipitation distribution characteristics during late spring to early summer, although it tends to underestimate the magnitude of precipitation. This dry bias is partly due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagation of convective systems in simulation. Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor. The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds inbetween, leading to less warm moist air transport from the Gulf to the central Great Plains. The simulated low-level horizontal convergence fields are less favorable than reanalysis data for upward motion and hence for convection development also. Therefore, careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project change of precipitation in future climate scenarios.
, Available online
, Manuscript accepted 21 July 2023, doi: 10.1007/s00376-023-3007-8
Abstract:
In the summer of 2022, China (especially the Yangtze River Valley, YRV) suffered its strongest heatwave (HW) event since 1961. In this study, we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV, focusing on the city of Shanghai. We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming. During mid-summer of 2022, an enhanced western Pacific subtropical high (WPSH) and anomalous double blockings over the Ural Mountains and Sea of Okhotsk, respectively, were associated with the persistently anomalous high pressure over the YRV, leading to the extreme HW. The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale. Also, the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern. Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH. At the subseasonal time scale, the anomalously frequent phases 2–5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden–Julian Oscillation suppressed the convection over the YRV and also contributed to the HW. Therefore, the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air–sea interaction at multiple time scales.
In the summer of 2022, China (especially the Yangtze River Valley, YRV) suffered its strongest heatwave (HW) event since 1961. In this study, we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV, focusing on the city of Shanghai. We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming. During mid-summer of 2022, an enhanced western Pacific subtropical high (WPSH) and anomalous double blockings over the Ural Mountains and Sea of Okhotsk, respectively, were associated with the persistently anomalous high pressure over the YRV, leading to the extreme HW. The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale. Also, the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern. Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH. At the subseasonal time scale, the anomalously frequent phases 2–5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden–Julian Oscillation suppressed the convection over the YRV and also contributed to the HW. Therefore, the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air–sea interaction at multiple time scales.
, Available online
, Manuscript accepted 14 July 2023, doi: 10.1007/s00376-023-3059-9
Abstract:
Atmospheric ammonia (NH3) is a chemically active trace gas which plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH3 concentration based on the absorption lines of NH3 in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH3 column from the Hyperspectral Infrared Atmospheric Sounder (HIRAS) onboard the Chinese FengYun (FY)-3D satellite and present the first atmospheric NH3 column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH3 hotspots around the world, e.g., India, West Africa, and East China, where large NH3 emissions exist. The HIRAS NH3 columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer (IASI) measurements, and we find that the two instruments observe a consistent NH3 global distribution, with correlation coefficient (R) values of 0.28-0.73. Finally, some remaining issues about the HIRAS NH3 retrieval are discussed.
Atmospheric ammonia (NH3) is a chemically active trace gas which plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH3 concentration based on the absorption lines of NH3 in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH3 column from the Hyperspectral Infrared Atmospheric Sounder (HIRAS) onboard the Chinese FengYun (FY)-3D satellite and present the first atmospheric NH3 column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH3 hotspots around the world, e.g., India, West Africa, and East China, where large NH3 emissions exist. The HIRAS NH3 columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer (IASI) measurements, and we find that the two instruments observe a consistent NH3 global distribution, with correlation coefficient (R) values of 0.28-0.73. Finally, some remaining issues about the HIRAS NH3 retrieval are discussed.
, Available online
, Manuscript accepted 12 July 2023, doi: 10.1007/s00376-023-3037-2
Abstract:
The variations of frontogenetic trend of cold filament induced by the cross-filament wind and wave fields are studied by a non-hydrostatic large eddy simulation. Five case studies are made with the different strengths of the wind and wave fields. The results show that the intense wind and wave fields further break the symmetries of submesoscale flow fields and suppress the levels of filament frontogenesis. The changes of secondary circulation directions, that is, the conversion between the convergence and divergence of the surface cross-filament currents with the downwelling and upwelling jets in the filament center, are associated with the inertial oscillation. The filament frontogenesis and frontolysis caused by the changes of secondary circulation directions may periodically sharpen and smooth the gradient of submesoscale flow fields. The lifecycle of cold filament may include the multiple stages of the filament frontogenesis and frontolysis.
The variations of frontogenetic trend of cold filament induced by the cross-filament wind and wave fields are studied by a non-hydrostatic large eddy simulation. Five case studies are made with the different strengths of the wind and wave fields. The results show that the intense wind and wave fields further break the symmetries of submesoscale flow fields and suppress the levels of filament frontogenesis. The changes of secondary circulation directions, that is, the conversion between the convergence and divergence of the surface cross-filament currents with the downwelling and upwelling jets in the filament center, are associated with the inertial oscillation. The filament frontogenesis and frontolysis caused by the changes of secondary circulation directions may periodically sharpen and smooth the gradient of submesoscale flow fields. The lifecycle of cold filament may include the multiple stages of the filament frontogenesis and frontolysis.
, Available online
, Manuscript accepted 04 July 2023, doi: 10.1007/s00376-023-2231-6
Abstract:
The cloud type product 2B-CLDCLASS-LIDAR based on CloudSat and CALIPSO from June 2006 to May 2017 is used to examine the temporal and spatial distribution characteristics and interannual variability of eight cloud types (high cloud, altostratus, altocumulus, stratus, stratocumulus, cumulus, nimbostratus, and deep convection) and three phases (ice, mixed, and water) in the Arctic. Possible reasons for the observed interannual variability are also discussed. The main conclusions are as follows: (1) More water clouds occur on the Atlantic side, and more ice clouds occur over continents. (2) The average spatial and seasonal distributions of cloud types show three patterns: high clouds and most cumuliform clouds are concentrated in low-latitude locations and peak in summer; altostratus and nimbostratus are concentrated over and around continents and are less abundant in summer; stratocumulus and stratus are concentrated near the inner Arctic and peak during spring and autumn. (3) Regional averaged interannual frequencies of ice clouds and altostratus clouds significantly decrease, while those of water clouds, altocumulus, and cumulus clouds increase significantly. (4) Significant features of the linear trends of cloud frequencies are mainly located over ocean areas. (5) The monthly water cloud frequency anomalies are positively correlated with air temperature in most of the troposphere, while those for ice clouds are negatively correlated. (6) The decrease in altostratus clouds is associated with the weakening of the Arctic front due to Arctic warming, while increased water vapor transport into the Arctic and higher atmospheric instability lead to more cumulus and altocumulus clouds.
The cloud type product 2B-CLDCLASS-LIDAR based on CloudSat and CALIPSO from June 2006 to May 2017 is used to examine the temporal and spatial distribution characteristics and interannual variability of eight cloud types (high cloud, altostratus, altocumulus, stratus, stratocumulus, cumulus, nimbostratus, and deep convection) and three phases (ice, mixed, and water) in the Arctic. Possible reasons for the observed interannual variability are also discussed. The main conclusions are as follows: (1) More water clouds occur on the Atlantic side, and more ice clouds occur over continents. (2) The average spatial and seasonal distributions of cloud types show three patterns: high clouds and most cumuliform clouds are concentrated in low-latitude locations and peak in summer; altostratus and nimbostratus are concentrated over and around continents and are less abundant in summer; stratocumulus and stratus are concentrated near the inner Arctic and peak during spring and autumn. (3) Regional averaged interannual frequencies of ice clouds and altostratus clouds significantly decrease, while those of water clouds, altocumulus, and cumulus clouds increase significantly. (4) Significant features of the linear trends of cloud frequencies are mainly located over ocean areas. (5) The monthly water cloud frequency anomalies are positively correlated with air temperature in most of the troposphere, while those for ice clouds are negatively correlated. (6) The decrease in altostratus clouds is associated with the weakening of the Arctic front due to Arctic warming, while increased water vapor transport into the Arctic and higher atmospheric instability lead to more cumulus and altocumulus clouds.
, Available online
, Manuscript accepted 04 July 2023, doi: 10.1007/s00376-023-2281-9
Abstract:
Based on the TRMM dataset, this paper compares the applicability of the improved MCE (minimum circumscribed ellipse), MBR (minimum bounding rectangle), and DIA (direct indexing area) methods for rain cell fitting. These three methods can reflect the geometric characteristics of clouds and apply geometric parameters to estimate the real dimensions of rain cells. The MCE method shows a major advantage in identifying the circumference of rain cells. The circumference of rain cells identified by MCE in most samples is smaller than that identified by DIA and MBR, and more similar to the observed rain cells. The area of rain cells identified by MBR is relatively robust. For rain cells composed of many pixels (N > 20), the overall performance is better than that of MCE, but the contribution of MBR to the best identification results, which have the shortest circumference and the smallest area, is less than that of MCE. The DIA method is best suited to small rain cells with a circumference of less than 100 km and an area of less than 120 km2, but the overall performance is mediocre. The MCE method tended to achieve the highest success at any angle, whereas there were fewer “best identification” results from the DIA or MBR more of the worst ones in the along-track direction and cross-track direction. By comprehensive comparison, MCE can obtain the best fitting results with the shortest circumference and the smallest area on behalf of the high filling effect for all sizes of rain cells.
Based on the TRMM dataset, this paper compares the applicability of the improved MCE (minimum circumscribed ellipse), MBR (minimum bounding rectangle), and DIA (direct indexing area) methods for rain cell fitting. These three methods can reflect the geometric characteristics of clouds and apply geometric parameters to estimate the real dimensions of rain cells. The MCE method shows a major advantage in identifying the circumference of rain cells. The circumference of rain cells identified by MCE in most samples is smaller than that identified by DIA and MBR, and more similar to the observed rain cells. The area of rain cells identified by MBR is relatively robust. For rain cells composed of many pixels (N > 20), the overall performance is better than that of MCE, but the contribution of MBR to the best identification results, which have the shortest circumference and the smallest area, is less than that of MCE. The DIA method is best suited to small rain cells with a circumference of less than 100 km and an area of less than 120 km2, but the overall performance is mediocre. The MCE method tended to achieve the highest success at any angle, whereas there were fewer “best identification” results from the DIA or MBR more of the worst ones in the along-track direction and cross-track direction. By comprehensive comparison, MCE can obtain the best fitting results with the shortest circumference and the smallest area on behalf of the high filling effect for all sizes of rain cells.
, Available online
, Manuscript accepted 03 July 2023, doi: 10.1007/s00376-023-3068-8
Abstract:
This paper studied a snow event over North China on June 21, 2017, using aircraft in-situ data, lagrangian analysis tool, and WRF simulations with different microphysical schemes to investigate the supercooled layer of Warm Conveyor Belts (WCBs). Base on the aircraft data, we exhibit a fine vertical structure of WCB cloud and highlighted a 1-2 km thin supercooled liquid water layer with a maximum Liquid Water Content (LWC) exceeding 0.5g kg-1 during the vertical aircraft observation. Although the main features of thermodynamic profiles were essentially captured by both schemes, the microphysical quantities exhibited large diversity in different microphysics schemes. The conventional Morrison two-moment scheme showed remarkable agreement with in-situ observation, both in terms of the thermodynamic structures and the supercooled liquid water layer. However, the microphysical structure, in terms of LWC and IWC, of the WCB cloud was not apparent in HUJI fast bin. To reduce this uncertainty, future work may focus on improving the representation of microphysics in bin schemes with in-situ data and using similar assumptions for all schemes to isolate the impact of physics.
This paper studied a snow event over North China on June 21, 2017, using aircraft in-situ data, lagrangian analysis tool, and WRF simulations with different microphysical schemes to investigate the supercooled layer of Warm Conveyor Belts (WCBs). Base on the aircraft data, we exhibit a fine vertical structure of WCB cloud and highlighted a 1-2 km thin supercooled liquid water layer with a maximum Liquid Water Content (LWC) exceeding 0.5g kg-1 during the vertical aircraft observation. Although the main features of thermodynamic profiles were essentially captured by both schemes, the microphysical quantities exhibited large diversity in different microphysics schemes. The conventional Morrison two-moment scheme showed remarkable agreement with in-situ observation, both in terms of the thermodynamic structures and the supercooled liquid water layer. However, the microphysical structure, in terms of LWC and IWC, of the WCB cloud was not apparent in HUJI fast bin. To reduce this uncertainty, future work may focus on improving the representation of microphysics in bin schemes with in-situ data and using similar assumptions for all schemes to isolate the impact of physics.
, Available online
, Manuscript accepted 03 July 2023, doi: 10.1007/s00376-023-2270-z
Abstract:
If an explicit time scheme is used in a numerical model, the size of the integration time step is typically limited by the spatial resolution. This study develops a regular latitude–longitude grid-based global three-dimensional tracer transport model that is computationally stable at large time-step sizes. The tracer model employs a finite-volume flux-form semi-Lagrangian (FFSL) transport scheme in the horizontal and an adaptively implicit algorithm in the vertical. The horizontal and vertical solvers are coupled via a straightforward operator-splitting technique. Both the finite-volume scheme’s one-dimensional slope-limiter and the adaptively implicit vertical solver’s first-order upwind scheme enforce monotonicity. The tracer model permits a large time-step size and is inherently conservative and monotonic. Idealized advection test cases demonstrate that the three-dimensional transport model performs very well in terms of accuracy, stability, and efficiency. It is possible to use this robust transport model in a global atmospheric dynamical core.
If an explicit time scheme is used in a numerical model, the size of the integration time step is typically limited by the spatial resolution. This study develops a regular latitude–longitude grid-based global three-dimensional tracer transport model that is computationally stable at large time-step sizes. The tracer model employs a finite-volume flux-form semi-Lagrangian (FFSL) transport scheme in the horizontal and an adaptively implicit algorithm in the vertical. The horizontal and vertical solvers are coupled via a straightforward operator-splitting technique. Both the finite-volume scheme’s one-dimensional slope-limiter and the adaptively implicit vertical solver’s first-order upwind scheme enforce monotonicity. The tracer model permits a large time-step size and is inherently conservative and monotonic. Idealized advection test cases demonstrate that the three-dimensional transport model performs very well in terms of accuracy, stability, and efficiency. It is possible to use this robust transport model in a global atmospheric dynamical core.
, Available online
, Manuscript accepted 27 June 2023, doi: 10.1007/s00376-023-3029-2
Abstract:
This study assesses the suitability of convolutional neural networks (CNNs) for downscaling precipitation over East Africa in the context of seasonal forecasting. To achieve this, we design a set of experiments that compare different CNN configurations and deployed the best-performing architecture to downscale one-month lead seasonal forecasts of June–July–August–September (JJAS) precipitation from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for 1982–2020. We also perform hyper-parameter optimization and introduce predictors over a larger area to include information about the main large-scale circulations that drive precipitation over the East Africa region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results show that the CNN-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme precipitation spatial patterns. Besides, CNN-based downscaling yields a much more accurate forecast of extreme and spell indicators and reduces the significant relative biases exhibited by the raw model predictions. Moreover, our results show that CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of East Africa. The results demonstrate the potential usefulness of CNN in downscaling seasonal precipitation predictions over East Africa, particularly in providing improved forecast products which are essential for end users.
This study assesses the suitability of convolutional neural networks (CNNs) for downscaling precipitation over East Africa in the context of seasonal forecasting. To achieve this, we design a set of experiments that compare different CNN configurations and deployed the best-performing architecture to downscale one-month lead seasonal forecasts of June–July–August–September (JJAS) precipitation from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for 1982–2020. We also perform hyper-parameter optimization and introduce predictors over a larger area to include information about the main large-scale circulations that drive precipitation over the East Africa region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results show that the CNN-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme precipitation spatial patterns. Besides, CNN-based downscaling yields a much more accurate forecast of extreme and spell indicators and reduces the significant relative biases exhibited by the raw model predictions. Moreover, our results show that CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of East Africa. The results demonstrate the potential usefulness of CNN in downscaling seasonal precipitation predictions over East Africa, particularly in providing improved forecast products which are essential for end users.
, Available online
, Manuscript accepted 27 June 2023, doi: 10.1007/s00376-023-3004-y
Abstract:
Quantifying the contributions to Arctic sea level (ASL) variability is critical to understand how the Arctic is responsing to ongoing climate change. Here, we use Ocean Reanalysis System 5 (ORAS5) reanalysis data and tide gauge and satellite altimetry observations to quantify contributions from different physical processes on the ASL variability. The ORAS5 reanalysis shows that the ASL is rising with a trend of 2.5 ± 0.3 mm yr−1 (95% confidence level) over 1979–2018, which can be attributed to four components: (i) the dominant component from the global sea level increase of 1.9 ± 0.5 mm yr−1, explaining 69.7% of the total variance of the ASL time series; (ii) the Arctic Oscillation–induced mass redistribution between the deep central basin and shallow shelves, with no significant trend and explaining 6.3% of the total variance; (iii) the steric sea level increase centering on the Beaufort Gyre region with a trend of 0.5 ± 0.1 mm yr−1 and explaining 29.1% of the total variance of the ASL time series; and (iv) the intrusion of Pacific water into the Arctic Ocean, with no significant trend and contributing 14.2% of the total ASL variability. Furthermore, the dramatic sea ice melting and the larger area of open water changes the impact of the large-scale atmospheric forcing on the ASL variability after 1995, and the ocean dynamic circulation plays a more important role in the ASL variability.
Quantifying the contributions to Arctic sea level (ASL) variability is critical to understand how the Arctic is responsing to ongoing climate change. Here, we use Ocean Reanalysis System 5 (ORAS5) reanalysis data and tide gauge and satellite altimetry observations to quantify contributions from different physical processes on the ASL variability. The ORAS5 reanalysis shows that the ASL is rising with a trend of 2.5 ± 0.3 mm yr−1 (95% confidence level) over 1979–2018, which can be attributed to four components: (i) the dominant component from the global sea level increase of 1.9 ± 0.5 mm yr−1, explaining 69.7% of the total variance of the ASL time series; (ii) the Arctic Oscillation–induced mass redistribution between the deep central basin and shallow shelves, with no significant trend and explaining 6.3% of the total variance; (iii) the steric sea level increase centering on the Beaufort Gyre region with a trend of 0.5 ± 0.1 mm yr−1 and explaining 29.1% of the total variance of the ASL time series; and (iv) the intrusion of Pacific water into the Arctic Ocean, with no significant trend and contributing 14.2% of the total ASL variability. Furthermore, the dramatic sea ice melting and the larger area of open water changes the impact of the large-scale atmospheric forcing on the ASL variability after 1995, and the ocean dynamic circulation plays a more important role in the ASL variability.
, Available online
, Manuscript accepted 21 June 2023, doi: 10.1007/s00376-023-3006-9
Abstract:
To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to “warm Arctic, cold East Asia” (WACE), this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere-land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble-member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble-mean and the preindustrial ensemble-mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter has a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) of Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce warming with larger magnitude. Observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.
To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to “warm Arctic, cold East Asia” (WACE), this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere-land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble-member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble-mean and the preindustrial ensemble-mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter has a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) of Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce warming with larger magnitude. Observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.
, Available online
, Manuscript accepted 21 June 2023, doi: 10.1007/s00376-023-2365-6
Abstract:
Observational analyses demonstrate that the Ural persistent positive height anomaly event (PAE) experienced a decadal increase around the year 2000, exhibiting a southward displacement afterward. These decadal variations are related to a large-scale circulation shift over the Eurasian Continent. The effects of underlying sea ice and sea surface temperature (SST) anomalies on the Ural PAE and the related atmospheric circulation were explored by Atmospheric Model Intercomparison Project (AMIP) experiments from the Coupled Model Intercomparison Project Phase 6 and by sensitivity experiments using the Atmospheric General Circulation Model (AGCM). The AMIP experiment results suggest that the underlying sea ice and SST anomalies play important roles. The individual contributions of sea ice loss in the Barents-Kara Seas and the SST anomalies linked to the phase transition of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) are further investigated by AGCM sensitivity experiments isolating the respective forcings. The sea ice decline in Barents-Kara Seas triggers an atmospheric wave train over the Eurasian mid-to-high latitudes with positive anomalies over the Urals, favoring the occurrence of Ural PAEs. The shift in the PDO to its negative phase triggers a wave train propagating downstream from the North Pacific. One positive anomaly lobe of the wave train is located over the Ural Mountains and increases the PAE there. The negative-to-positive transition of the AMO phase since the late-1990s causes positive 500-hPa height anomalies south of the Ural Mountains, which promote a southward shift of Ural PAE.
Observational analyses demonstrate that the Ural persistent positive height anomaly event (PAE) experienced a decadal increase around the year 2000, exhibiting a southward displacement afterward. These decadal variations are related to a large-scale circulation shift over the Eurasian Continent. The effects of underlying sea ice and sea surface temperature (SST) anomalies on the Ural PAE and the related atmospheric circulation were explored by Atmospheric Model Intercomparison Project (AMIP) experiments from the Coupled Model Intercomparison Project Phase 6 and by sensitivity experiments using the Atmospheric General Circulation Model (AGCM). The AMIP experiment results suggest that the underlying sea ice and SST anomalies play important roles. The individual contributions of sea ice loss in the Barents-Kara Seas and the SST anomalies linked to the phase transition of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) are further investigated by AGCM sensitivity experiments isolating the respective forcings. The sea ice decline in Barents-Kara Seas triggers an atmospheric wave train over the Eurasian mid-to-high latitudes with positive anomalies over the Urals, favoring the occurrence of Ural PAEs. The shift in the PDO to its negative phase triggers a wave train propagating downstream from the North Pacific. One positive anomaly lobe of the wave train is located over the Ural Mountains and increases the PAE there. The negative-to-positive transition of the AMO phase since the late-1990s causes positive 500-hPa height anomalies south of the Ural Mountains, which promote a southward shift of Ural PAE.
, Available online
, Manuscript accepted 21 June 2023, doi: 10.1007/s00376-023-2363-8
Abstract:
The spring atmospheric heat source (AHS) over the Tibetan Plateau (TP) has been suggested to affect the Asian summer monsoon and summer precipitation over South China. However, its influence on the summer precipitation in Northeast China (NEC) remains unknown. The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study. Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation, and higher soil moisture in the Yellow River Valley‒North China region (YRVNC) acts as a bridge. During spring, the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC. Thus, soil moisture increases, which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat. Owing to the memory of soil moisture, the lower spring sensible heat over the YRVNC can last until mid-summer, decrease the land–sea thermal contrast, and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific. This modulates the East Asia–Pacific teleconnection pattern, which leads to a cyclonic anomaly and excessive summer precipitation over NEC.
The spring atmospheric heat source (AHS) over the Tibetan Plateau (TP) has been suggested to affect the Asian summer monsoon and summer precipitation over South China. However, its influence on the summer precipitation in Northeast China (NEC) remains unknown. The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study. Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation, and higher soil moisture in the Yellow River Valley‒North China region (YRVNC) acts as a bridge. During spring, the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC. Thus, soil moisture increases, which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat. Owing to the memory of soil moisture, the lower spring sensible heat over the YRVNC can last until mid-summer, decrease the land–sea thermal contrast, and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific. This modulates the East Asia–Pacific teleconnection pattern, which leads to a cyclonic anomaly and excessive summer precipitation over NEC.
, Available online
, Manuscript accepted 13 June 2023, doi: 10.1007/s00376-023-3084-8
Abstract:
Understanding the structure of Tropical Cyclone (TC) hydrometeors is crucial for detecting the changes of the distribution and intensity of precipitation. In this study, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) brightness temperature and cloud-dependent one-dimensional variational (1DVAR) algorithm are used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol. ARMS (Advanced Radiative Transfer Modeling System) is used to calculate the Jacobian and degrees of freedom (∆DOF) of cloud water, rainwater, and graupel for different channels of GMI. The retrieval results were compared with Dual-frequency Precipitation Radar (DPR), GMI 2A, and IMERG products. It is shown that from all channels of GMI, rainwater has the highest ∆DOF, which is 1.72. According to radiance Jacobian to atmospheric state variables, cloud water emission dominates its scattering in convective condition. For rainwater, the emission of channels 1 to 4 dominates scattering. Compared with GMI 2A precipitation product, the 1DVAR precipitation rate has a higher correlation coefficient (0.713) with the IMERG product and can better reflect the location of TC precipitation. Near the TC eyewall, the highest radar echo top indicates strong convection. Near the melting layer where Ka-band attenuation is strong, the double frequency difference of DPR data reflects the location of the melting. DPR DSD product shows that there is a significant increase in particle size below the melting layer in spiral rain band. Thus, the particle size may be one of the main reasons for the smaller rainwater below the melting layer retrieved from 1DVAR.
Understanding the structure of Tropical Cyclone (TC) hydrometeors is crucial for detecting the changes of the distribution and intensity of precipitation. In this study, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) brightness temperature and cloud-dependent one-dimensional variational (1DVAR) algorithm are used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol. ARMS (Advanced Radiative Transfer Modeling System) is used to calculate the Jacobian and degrees of freedom (∆DOF) of cloud water, rainwater, and graupel for different channels of GMI. The retrieval results were compared with Dual-frequency Precipitation Radar (DPR), GMI 2A, and IMERG products. It is shown that from all channels of GMI, rainwater has the highest ∆DOF, which is 1.72. According to radiance Jacobian to atmospheric state variables, cloud water emission dominates its scattering in convective condition. For rainwater, the emission of channels 1 to 4 dominates scattering. Compared with GMI 2A precipitation product, the 1DVAR precipitation rate has a higher correlation coefficient (0.713) with the IMERG product and can better reflect the location of TC precipitation. Near the TC eyewall, the highest radar echo top indicates strong convection. Near the melting layer where Ka-band attenuation is strong, the double frequency difference of DPR data reflects the location of the melting. DPR DSD product shows that there is a significant increase in particle size below the melting layer in spiral rain band. Thus, the particle size may be one of the main reasons for the smaller rainwater below the melting layer retrieved from 1DVAR.
, Available online
, Manuscript accepted 12 June 2023, doi: 10.1007/s00376-023-3023-8
Abstract:
This study investigates the relationship between the persistence and the zonal scale of atmospheric dipolar modes (DMs). Results from the daily data of ERA5 and the long-term output of an idealized atmospheric model show that the atmospheric DMs with a broader (narrower) zonal scale dipolar structure possess a longer (shorter) persistence. A detailed vorticity budget analysis indicates that the persistence of a hemispheric-scale DM (1/1 DM) and a regional or sectoral DM (1/8 DM) in the model both largely rely on the persistence of the nonlinear eddy forcing. Linear terms can indirectly reduce the persistence of the anomalous nonlinear eddy forcing in a 1/8 DM by modifying the baroclinicity via the arousal of anomalous vertical motions. Therefore, the atmospheric DMs with a broader (narrower) zonal scale possess a longer (shorter) persistence because the effects of the linear terms are less (more) pronounced when the atmospheric DMs have better (worse) zonal symmetry. Further analyses show that the positive eddy feedback effect is weak or even absent in a 1/8 DM and the high-frequency eddy forcing acts more like a concomitant phenomenon rather than a leading driving factor for a 1/8 DM. Thus, the hemispheric-scale DM and the regional or sectoral DMs are different, not only in their persistence but also in their dynamics.
This study investigates the relationship between the persistence and the zonal scale of atmospheric dipolar modes (DMs). Results from the daily data of ERA5 and the long-term output of an idealized atmospheric model show that the atmospheric DMs with a broader (narrower) zonal scale dipolar structure possess a longer (shorter) persistence. A detailed vorticity budget analysis indicates that the persistence of a hemispheric-scale DM (1/1 DM) and a regional or sectoral DM (1/8 DM) in the model both largely rely on the persistence of the nonlinear eddy forcing. Linear terms can indirectly reduce the persistence of the anomalous nonlinear eddy forcing in a 1/8 DM by modifying the baroclinicity via the arousal of anomalous vertical motions. Therefore, the atmospheric DMs with a broader (narrower) zonal scale possess a longer (shorter) persistence because the effects of the linear terms are less (more) pronounced when the atmospheric DMs have better (worse) zonal symmetry. Further analyses show that the positive eddy feedback effect is weak or even absent in a 1/8 DM and the high-frequency eddy forcing acts more like a concomitant phenomenon rather than a leading driving factor for a 1/8 DM. Thus, the hemispheric-scale DM and the regional or sectoral DMs are different, not only in their persistence but also in their dynamics.
, Available online
, Manuscript accepted 08 June 2023, doi: 10.1007/s00376-023-3010-0
Abstract:
Utilizing the Community Atmosphere Model, version 4, the influence of Arctic sea-ice concentration (SIC) on the extended-range prediction of three simulated cold events (CEs) in East Asia is investigated. Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia. The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale. It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad, as compared with random SIC perturbations under the same constraint. Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process, and then influence the remote temperature by horizontal advection and vertical convection terms. Consequently, the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains, leading to the largest prediction uncertainty of the CEs in the fourth pentad. These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill.
Utilizing the Community Atmosphere Model, version 4, the influence of Arctic sea-ice concentration (SIC) on the extended-range prediction of three simulated cold events (CEs) in East Asia is investigated. Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia. The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale. It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad, as compared with random SIC perturbations under the same constraint. Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process, and then influence the remote temperature by horizontal advection and vertical convection terms. Consequently, the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains, leading to the largest prediction uncertainty of the CEs in the fourth pentad. These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill.
, Available online
, Manuscript accepted 07 June 2023, doi: 10.1007/s00376-023-2234-3
Abstract:
Global gridded crop models (GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national- and provincial-scale evaluation of the simulations by 13 GGCMs [12 from the GGCM Intercomparison (GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops (wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national- and provincial-scale crop yield prediction in China.
Global gridded crop models (GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national- and provincial-scale evaluation of the simulations by 13 GGCMs [12 from the GGCM Intercomparison (GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops (wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national- and provincial-scale crop yield prediction in China.
, Available online
, Manuscript accepted 07 June 2023, doi: 10.1007/s00376-023-3036-3
Abstract:
Evapotranspiration (ET) is a crucial variable in the terrestrial water, carbon, and energy cycles. At present, a large number of multisource ET products exist. Due to sparse observations, however, great challenges exist in the evaluation and integration of ET products in remote and complex areas such as the Tibetan Plateau (TP). In this paper, the applicability of the multiple collocation (MC) method over the TP is evaluated for the first time, and the uncertainty of multisource ET products (based on reanalysis, remote sensing, and land surface models) is further analyzed, which provides a theoretical basis for ET data fusion. The results show that 1) ET uncertainties quantified via the MC method are lower in RS-based ET products (5.95 vs. 7.06 mm month–1) than in LSM ET products (10.22 vs. 17.97 mm month–1) and reanalysis ET estimates (7.27 vs. 12.26 mm month–1). 2) A multisource evapotranspiration (MET) dataset is generated at a monthly temporal scale with a spatial resolution of 0.25° across the TP during 2005–15. MET has better performance than any individual product. 3) Based on the fusion product, the total ET amount over the TP and its patterns of spatiotemporal variability are clearly identified. The annual total ET over the entire TP is approximately 380.60 mm. Additionally, an increasing trend of 1.59±0.85 mm yr–1 over the TP is shown during 2005–15. This study provides a basis for future studies on water and energy cycles and water resource management over the TP and surrounding regions.
Evapotranspiration (ET) is a crucial variable in the terrestrial water, carbon, and energy cycles. At present, a large number of multisource ET products exist. Due to sparse observations, however, great challenges exist in the evaluation and integration of ET products in remote and complex areas such as the Tibetan Plateau (TP). In this paper, the applicability of the multiple collocation (MC) method over the TP is evaluated for the first time, and the uncertainty of multisource ET products (based on reanalysis, remote sensing, and land surface models) is further analyzed, which provides a theoretical basis for ET data fusion. The results show that 1) ET uncertainties quantified via the MC method are lower in RS-based ET products (5.95 vs. 7.06 mm month–1) than in LSM ET products (10.22 vs. 17.97 mm month–1) and reanalysis ET estimates (7.27 vs. 12.26 mm month–1). 2) A multisource evapotranspiration (MET) dataset is generated at a monthly temporal scale with a spatial resolution of 0.25° across the TP during 2005–15. MET has better performance than any individual product. 3) Based on the fusion product, the total ET amount over the TP and its patterns of spatiotemporal variability are clearly identified. The annual total ET over the entire TP is approximately 380.60 mm. Additionally, an increasing trend of 1.59±0.85 mm yr–1 over the TP is shown during 2005–15. This study provides a basis for future studies on water and energy cycles and water resource management over the TP and surrounding regions.
, Available online
, Manuscript accepted 02 June 2023, doi: 10.1007/s00376-023-3005-x
Abstract:
El Niño–Southern Oscillation (ENSO) exhibits a distinctive phase locking characteristic, as expressed onset in boreal spring, developing during summer and autumn, reaching its peak towards winter and decaying over the next spring. Several studies have demonstrated that this feature arises as a result of seasonal variation of the sea surface temperature (SST) growth rate of ENSO. The bias for simulating the phase locking of ENSO by many state-of-the-art climate models is also attributed to the unrealistic depiction of the growth rate. In this study, the seasonal variation of SST growth rate in the Niño3.4 region (5°S-5°N, 120°W-170°W) is estimated in detail based on the mixed layer heat budget equation and recharge oscillator model during 1981-2020. It is suggested that considering the variation of mixed layer depth is essential to the diagnostic processes. The estimated growth rate has a remarkable seasonal cycle with the minimum occurring in spring and the maximum in autumn. More specifically, the growth rate derived from the meridional advection (surface heat flux) is positive (negative) throughout the year. The vertical diffusion generally serves as a negative contribution to the evolution of growth rate and the magnitude of vertical entrainment presents to be the smallest. Analysis indicates that the zonal advective feedback regulated by the meridional immigration of intertropical convergence zone which lies in the southernmost in February and marches northernmost in September dominates the seasonal variation of SST growth rate.
El Niño–Southern Oscillation (ENSO) exhibits a distinctive phase locking characteristic, as expressed onset in boreal spring, developing during summer and autumn, reaching its peak towards winter and decaying over the next spring. Several studies have demonstrated that this feature arises as a result of seasonal variation of the sea surface temperature (SST) growth rate of ENSO. The bias for simulating the phase locking of ENSO by many state-of-the-art climate models is also attributed to the unrealistic depiction of the growth rate. In this study, the seasonal variation of SST growth rate in the Niño3.4 region (5°S-5°N, 120°W-170°W) is estimated in detail based on the mixed layer heat budget equation and recharge oscillator model during 1981-2020. It is suggested that considering the variation of mixed layer depth is essential to the diagnostic processes. The estimated growth rate has a remarkable seasonal cycle with the minimum occurring in spring and the maximum in autumn. More specifically, the growth rate derived from the meridional advection (surface heat flux) is positive (negative) throughout the year. The vertical diffusion generally serves as a negative contribution to the evolution of growth rate and the magnitude of vertical entrainment presents to be the smallest. Analysis indicates that the zonal advective feedback regulated by the meridional immigration of intertropical convergence zone which lies in the southernmost in February and marches northernmost in September dominates the seasonal variation of SST growth rate.
, Available online
, Manuscript accepted 01 June 2023, doi: 10.1007/s00376-023-2257-9
Abstract:
Mathematical modeling of the interaction between solar radiation and the Earth’s atmosphere is formalized by the radiative transfer equation (RTE), whose resolution calls for two-stream approximations among other methods. This paper proposes a new two-stream approximation of the RTE with the development of the phase function and the intensity into a third-order series of Legendre polynomials. This new approach, which adds one more term in the expression of the intensity and the phase function, allows in the conditions of a plane parallel atmosphere a new mathematical formulation of γ parameters. It is then compared to the Eddington, Hemispheric Constant, Quadrature, Combined Delta Function and Modified Eddington, and second-order approximation methods with reference to the Discrete Ordinate (Disort) method (\begin{document}$ \delta $\end{document} ![]()
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Mathematical modeling of the interaction between solar radiation and the Earth’s atmosphere is formalized by the radiative transfer equation (RTE), whose resolution calls for two-stream approximations among other methods. This paper proposes a new two-stream approximation of the RTE with the development of the phase function and the intensity into a third-order series of Legendre polynomials. This new approach, which adds one more term in the expression of the intensity and the phase function, allows in the conditions of a plane parallel atmosphere a new mathematical formulation of γ parameters. It is then compared to the Eddington, Hemispheric Constant, Quadrature, Combined Delta Function and Modified Eddington, and second-order approximation methods with reference to the Discrete Ordinate (Disort) method (
, Available online
, Manuscript accepted 26 May 2023, doi: 10.1007/s00376-023-3031-8
Abstract:
The mechanical influences involved in the interaction between the Antarctic sea ice and ocean surface current (OSC) on the subpolar Southern Ocean have been systematically investigated for the first time by conducting two simulations that include and exclude the OSC in the calculation of the ice-ocean stress (IOS), using an eddy-permitting coupled ocean-sea ice global model. By comparing the results of these two experiments, significant increases of 5%, 27%, and 24%, were found in the subpolar Southern Ocean when excluding the OSC in the IOS calculation for the ocean surface stress, upwelling, and downwelling, respectively. Excluding the OSC in the IOS calculation also visibly strengthens the total mechanical energy input to the OSC by about 16%, and increases the eddy kinetic energy and mean kinetic energy by about 38% and 12%, respectively. Moreover, the response of the meridional overturning circulation in the Southern Ocean yields respective increases of about 16% and 15% for the upper and lower branches; and the subpolar gyres are also found to considerably intensify, by about 12%, 11%, and 11% in the Weddell Gyre, the Ross Gyre, and the Australian-Antarctic Gyre, respectively. The strengthened ocean circulations and Ekman pumping result in a warmer sea surface temperature (SST), and hence an incremental surface heat loss. The increased sea ice drift and warm SST lead to an expansion of the sea ice area and a reduction of sea ice volume. These results emphasize the importance of OSCs in the air-sea-ice interactions on the global ocean circulations and the mass balance of Antarctic ice shelves, and this component may become more significant as the rapid change of Antarctic sea ice.
The mechanical influences involved in the interaction between the Antarctic sea ice and ocean surface current (OSC) on the subpolar Southern Ocean have been systematically investigated for the first time by conducting two simulations that include and exclude the OSC in the calculation of the ice-ocean stress (IOS), using an eddy-permitting coupled ocean-sea ice global model. By comparing the results of these two experiments, significant increases of 5%, 27%, and 24%, were found in the subpolar Southern Ocean when excluding the OSC in the IOS calculation for the ocean surface stress, upwelling, and downwelling, respectively. Excluding the OSC in the IOS calculation also visibly strengthens the total mechanical energy input to the OSC by about 16%, and increases the eddy kinetic energy and mean kinetic energy by about 38% and 12%, respectively. Moreover, the response of the meridional overturning circulation in the Southern Ocean yields respective increases of about 16% and 15% for the upper and lower branches; and the subpolar gyres are also found to considerably intensify, by about 12%, 11%, and 11% in the Weddell Gyre, the Ross Gyre, and the Australian-Antarctic Gyre, respectively. The strengthened ocean circulations and Ekman pumping result in a warmer sea surface temperature (SST), and hence an incremental surface heat loss. The increased sea ice drift and warm SST lead to an expansion of the sea ice area and a reduction of sea ice volume. These results emphasize the importance of OSCs in the air-sea-ice interactions on the global ocean circulations and the mass balance of Antarctic ice shelves, and this component may become more significant as the rapid change of Antarctic sea ice.
, Available online
, Manuscript accepted 26 May 2023, doi: 10.1007/s00376-023-3013-x
Abstract:
Based on eddy covariance (EC) measurements during 2016–2020, the effects of sky conditions on the net ecosystem productivity (NEP) over a subtropical “floating blanket” wetland were investigated. Sky conditions were divided into overcast, cloudy, and sunny conditions. On the half-hourly timescale, the daytime NEP responded more rapidly to the changes in the total photosynthetic active radiation (PARt) under overcast and cloudy skies than that under sunny skies. The increase in the apparent quantum yield under overcast and cloudy conditions was the greatest in spring and the least in summer. Additionally, lower atmospheric vapor pressure deficit (VPD) and moderate air temperature were more conducive to enhancing the apparent quantum yield under cloudy skies. On the daily timescale, NEP and the gross primary production (GPP) were higher under cloudy or sunny conditions than those under overcast conditions across seasons. The daily NEP and GPP during the wet season peaked under cloudy skies. The daily ecosystem light use efficiency (LUE) and water use efficiency (WUE) during the wet season also changed with sky conditions and reached their maximum under overcast and cloudy skies, respectively. The diffuse photosynthetic active radiation (PARd) and air temperature were primarily responsible for the variation of daily NEP from half-hourly to monthly timescales, and the direct photosynthetic active radiation (PARb) had a secondary effect on NEP. Under sunny conditions, PARb and air temperature were the dominant factors controlling daily NEP. While daily NEP was mainly controlled by PARd under cloudy and overcast conditions.
Based on eddy covariance (EC) measurements during 2016–2020, the effects of sky conditions on the net ecosystem productivity (NEP) over a subtropical “floating blanket” wetland were investigated. Sky conditions were divided into overcast, cloudy, and sunny conditions. On the half-hourly timescale, the daytime NEP responded more rapidly to the changes in the total photosynthetic active radiation (PARt) under overcast and cloudy skies than that under sunny skies. The increase in the apparent quantum yield under overcast and cloudy conditions was the greatest in spring and the least in summer. Additionally, lower atmospheric vapor pressure deficit (VPD) and moderate air temperature were more conducive to enhancing the apparent quantum yield under cloudy skies. On the daily timescale, NEP and the gross primary production (GPP) were higher under cloudy or sunny conditions than those under overcast conditions across seasons. The daily NEP and GPP during the wet season peaked under cloudy skies. The daily ecosystem light use efficiency (LUE) and water use efficiency (WUE) during the wet season also changed with sky conditions and reached their maximum under overcast and cloudy skies, respectively. The diffuse photosynthetic active radiation (PARd) and air temperature were primarily responsible for the variation of daily NEP from half-hourly to monthly timescales, and the direct photosynthetic active radiation (PARb) had a secondary effect on NEP. Under sunny conditions, PARb and air temperature were the dominant factors controlling daily NEP. While daily NEP was mainly controlled by PARd under cloudy and overcast conditions.
, Available online
, Manuscript accepted 22 May 2023, doi: 10.1007/s00376-023-2392-3
Abstract:
This study investigates the relationship between circulation patterns and austral summer temperature anomalies in southern Africa. The results show that the formation of continental lows tends to increase the thickness of the lower atmosphere. Further, the distinct variabilities of high and low pressure under the circulation types, influence air mass advection from the adjacent oceans, as well as atmospheric stability over land. Stronger anticyclonic circulation at the western branch of the Mascarene high-pressure system enhances the low-level cold air advection by southeast winds, decreases the thickness, and lowers the temperature over a majority of the land in southern Africa. Conversely, a weaker Mascarene High, coupled with enhanced cyclonic activity in the southwest Indian Ocean increases low-level warm air advection and increases temperature anomalies over vast regions in southern Africa. The ridging of a closed South Atlantic anticyclone at the southern coast of southern Africa results in colder temperatures near the tip of southern Africa due to enhanced low-level cold air advection by southeast winds. However, when the ridge is weak and westerly winds dominate the southern coast of southern Africa, these areas experience temperature increases. The northward track of the Southern Hemisphere mid-latitude cyclone, which can be linked to the negative Southern Annular Mode, reduces the temperature in the southwestern part of southern Africa. Also, during the analysis period, El Niño were associated with temperature increases over the central parts of southern Africa; while the positive Indian Ocean dipole was linked to a temperature increase over the northeastern, northwestern, and southwestern parts of southern Africa.
This study investigates the relationship between circulation patterns and austral summer temperature anomalies in southern Africa. The results show that the formation of continental lows tends to increase the thickness of the lower atmosphere. Further, the distinct variabilities of high and low pressure under the circulation types, influence air mass advection from the adjacent oceans, as well as atmospheric stability over land. Stronger anticyclonic circulation at the western branch of the Mascarene high-pressure system enhances the low-level cold air advection by southeast winds, decreases the thickness, and lowers the temperature over a majority of the land in southern Africa. Conversely, a weaker Mascarene High, coupled with enhanced cyclonic activity in the southwest Indian Ocean increases low-level warm air advection and increases temperature anomalies over vast regions in southern Africa. The ridging of a closed South Atlantic anticyclone at the southern coast of southern Africa results in colder temperatures near the tip of southern Africa due to enhanced low-level cold air advection by southeast winds. However, when the ridge is weak and westerly winds dominate the southern coast of southern Africa, these areas experience temperature increases. The northward track of the Southern Hemisphere mid-latitude cyclone, which can be linked to the negative Southern Annular Mode, reduces the temperature in the southwestern part of southern Africa. Also, during the analysis period, El Niño were associated with temperature increases over the central parts of southern Africa; while the positive Indian Ocean dipole was linked to a temperature increase over the northeastern, northwestern, and southwestern parts of southern Africa.
, Available online
, Manuscript accepted 22 May 2023, doi: 10.1007/s00376-023-3002-0
Abstract:
One of the basic characteristics of Earth’s modern climate is that the Northern Hemisphere (NH) is climatologically warmer than the Southern Hemisphere (SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average (0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from −0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the cross-equatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents. Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.
One of the basic characteristics of Earth’s modern climate is that the Northern Hemisphere (NH) is climatologically warmer than the Southern Hemisphere (SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average (0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from −0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the cross-equatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents. Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.
, Available online
, Manuscript accepted 19 May 2023, doi: 10.1007/s00376-023-2371-8
Abstract:
The influence of Arctic sea ice concentration (SIC) on the subseasonal prediction of the North Atlantic Oscillation (NAO) event is investigated by utilizing the Community Atmospheric Model version 4. The optimal Arctic SIC perturbations which exert the greatest influence on the onset of an NAO event from a lead of three pentads (15 days) are obtained with a conditional nonlinear optimal perturbation approach. Numerical results show that there are two types of optimal Arctic SIC perturbations for each NAO event, with one weakening event (marked as type-1) and another strengthening event (marked as type-2). For positive NAO events, type-1 optimal SIC perturbations mainly show positive SIC anomalies in the Greenland, Barents, and Okhotsk Seas, while type-2 perturbations mainly feature negative SIC anomalies in these regions. For negative NAO events, the optimal SIC perturbations have almost opposite patterns to those in positive events, although there are some differences among these SIC perturbations due to different atmospheric initial conditions. Further diagnosis reveals that the optimal Arctic SIC perturbations first modify the surface turbulent heat flux and the temperature in the lower troposphere via diabatic processes. Afterward, the temperature in the low troposphere is mainly affected by dynamic advection. Finally, potential vorticity advection plays a crucial role in the 500-hPa geopotential height prediction in the northern North Atlantic sector during pentad 4, which influences NAO event prediction. These results highlight the importance of Arctic SIC on NAO event prediction and the spatial characteristics of the SIC perturbations may provide scientific support for target observations of SIC in improving NAO subseasonal predictions.
The influence of Arctic sea ice concentration (SIC) on the subseasonal prediction of the North Atlantic Oscillation (NAO) event is investigated by utilizing the Community Atmospheric Model version 4. The optimal Arctic SIC perturbations which exert the greatest influence on the onset of an NAO event from a lead of three pentads (15 days) are obtained with a conditional nonlinear optimal perturbation approach. Numerical results show that there are two types of optimal Arctic SIC perturbations for each NAO event, with one weakening event (marked as type-1) and another strengthening event (marked as type-2). For positive NAO events, type-1 optimal SIC perturbations mainly show positive SIC anomalies in the Greenland, Barents, and Okhotsk Seas, while type-2 perturbations mainly feature negative SIC anomalies in these regions. For negative NAO events, the optimal SIC perturbations have almost opposite patterns to those in positive events, although there are some differences among these SIC perturbations due to different atmospheric initial conditions. Further diagnosis reveals that the optimal Arctic SIC perturbations first modify the surface turbulent heat flux and the temperature in the lower troposphere via diabatic processes. Afterward, the temperature in the low troposphere is mainly affected by dynamic advection. Finally, potential vorticity advection plays a crucial role in the 500-hPa geopotential height prediction in the northern North Atlantic sector during pentad 4, which influences NAO event prediction. These results highlight the importance of Arctic SIC on NAO event prediction and the spatial characteristics of the SIC perturbations may provide scientific support for target observations of SIC in improving NAO subseasonal predictions.
, Available online
, Manuscript accepted 15 May 2023, doi: 10.1007/s00376-023-2340-2
Abstract:
Capabilities to assimilate Geostationary Operational Environmental Satellite “R-series” (GOES-R) Geostationary Lightning Mapper (GLM) flash extent density (FED) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter (GSI-EnKF) framework were previously developed and tested with a mesoscale convective system (MCS) case. In this study, such capabilities are further developed to assimilate GOES GLM FED data within the GSI ensemble-variational (EnVar) hybrid data assimilation (DA) framework. The results of assimilating the GLM FED data using 3DVar, and pure En3DVar (PEn3DVar, using 100% ensemble covariance and no static covariance) are compared with those of EnKF/DfEnKF for a supercell storm case. The focus of this study is to validate the correctness and evaluate the performance of the new implementation rather than comparing the performance of FED DA among different DA schemes. Only the results of 3DVar and pEn3DVar are examined and compared with EnKF/DfEnKF. Assimilation of a single FED observation shows that the magnitude and horizontal extent of the analysis increments from PEn3DVar are generally larger than from EnKF, which is mainly caused by using different localization strategies in EnFK/DfEnKF and PEn3DVar as well as the integration limits of the graupel mass in the observation operator. Overall, the forecast performance of PEn3DVar is comparable to EnKF/DfEnKF, suggesting correct implementation.
Capabilities to assimilate Geostationary Operational Environmental Satellite “R-series” (GOES-R) Geostationary Lightning Mapper (GLM) flash extent density (FED) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter (GSI-EnKF) framework were previously developed and tested with a mesoscale convective system (MCS) case. In this study, such capabilities are further developed to assimilate GOES GLM FED data within the GSI ensemble-variational (EnVar) hybrid data assimilation (DA) framework. The results of assimilating the GLM FED data using 3DVar, and pure En3DVar (PEn3DVar, using 100% ensemble covariance and no static covariance) are compared with those of EnKF/DfEnKF for a supercell storm case. The focus of this study is to validate the correctness and evaluate the performance of the new implementation rather than comparing the performance of FED DA among different DA schemes. Only the results of 3DVar and pEn3DVar are examined and compared with EnKF/DfEnKF. Assimilation of a single FED observation shows that the magnitude and horizontal extent of the analysis increments from PEn3DVar are generally larger than from EnKF, which is mainly caused by using different localization strategies in EnFK/DfEnKF and PEn3DVar as well as the integration limits of the graupel mass in the observation operator. Overall, the forecast performance of PEn3DVar is comparable to EnKF/DfEnKF, suggesting correct implementation.
, Available online
, Manuscript accepted 15 May 2023, doi: 10.1007/s00376-023-2296-2
Abstract:
Thermal processes on the Tibetan Plateau (TP) influence atmospheric conditions on regional and global scales. Given this, previous work has shown that soil moisture−driven surface flux variations feed back onto the atmosphere. Whilst soil moisture is a source of atmospheric predictability, no study has evaluated soil moisture−atmosphere coupling on the TP in general circulation models (GCMs). In this study, we use several analysis techniques to assess soil moisture−atmosphere coupling in CMIP6 simulations including: instantaneous coupling indices; analysis of flux and atmospheric behaviour during dry spells; and a quantification of the preference for convection over drier soils. Through these metrics we partition feedbacks into their atmospheric and terrestrial components. Consistent with previous global studies, we conclude substantial inter-model differences in the representation of soil moisture−atmosphere coupling, and that most models underestimate such feedbacks. Focusing on dry spell analysis, most models underestimate increased sensible heat during periods of rainfall deficiency. For example, the model-mean bias in anomalous sensible heat flux is 10 W m−2 (≈25%) smaller compared to observations. Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response. We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection. The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture−driven predictability. To improve the representation of land−atmosphere feedbacks requires developments in not only atmospheric modelling, but also surface processes, as we find weak relationships between rainfall biases and coupling indexes.
Thermal processes on the Tibetan Plateau (TP) influence atmospheric conditions on regional and global scales. Given this, previous work has shown that soil moisture−driven surface flux variations feed back onto the atmosphere. Whilst soil moisture is a source of atmospheric predictability, no study has evaluated soil moisture−atmosphere coupling on the TP in general circulation models (GCMs). In this study, we use several analysis techniques to assess soil moisture−atmosphere coupling in CMIP6 simulations including: instantaneous coupling indices; analysis of flux and atmospheric behaviour during dry spells; and a quantification of the preference for convection over drier soils. Through these metrics we partition feedbacks into their atmospheric and terrestrial components. Consistent with previous global studies, we conclude substantial inter-model differences in the representation of soil moisture−atmosphere coupling, and that most models underestimate such feedbacks. Focusing on dry spell analysis, most models underestimate increased sensible heat during periods of rainfall deficiency. For example, the model-mean bias in anomalous sensible heat flux is 10 W m−2 (≈25%) smaller compared to observations. Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response. We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection. The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture−driven predictability. To improve the representation of land−atmosphere feedbacks requires developments in not only atmospheric modelling, but also surface processes, as we find weak relationships between rainfall biases and coupling indexes.
, Available online
, Manuscript accepted 15 May 2023, doi: 10.1007/s00376-023-2342-0
Abstract:
The spatial distribution of summer precipitation anomalies over eastern China often shows a dipole pattern, with anti-phased precipitation anomalies between southern China and northern China, known as the “southern flooding and northern drought” (SF-ND) pattern. In 2015, China experienced heavy rainfall in the south and the worst drought since 1979 in the north, which caused huge social and economic losses. Using reanalysis data, the atmospheric circulation anomalies and possible mechanisms related to the summer precipitation anomalies in 2015 were examined. The results showed that both El Niño and certain atmospheric teleconnections, including the Pacific Japan/East Asia Pacific (PJ/EAP), Eurasia pattern (EU), British–Baikal Corridor pattern (BBC), and Silk Road mode (SR), contributed to the dipole pattern of precipitation anomalies. The combination of these factors caused a southwards shift of the western Pacific subtropical high (WPSH) and a weakening of the East Asian summer monsoon. Consequently, it was difficult for the monsoon front and associated rain band to migrate northwards, which meant that less precipitation occurred in northern China while more precipitation occurred in southern China. This resulted in the SF-ND event. Moreover, further analysis revealed that global sea surface temperature anomalies (SSTAs) or sea-ice anomalies were key to stimulating these atmospheric teleconnections.
The spatial distribution of summer precipitation anomalies over eastern China often shows a dipole pattern, with anti-phased precipitation anomalies between southern China and northern China, known as the “southern flooding and northern drought” (SF-ND) pattern. In 2015, China experienced heavy rainfall in the south and the worst drought since 1979 in the north, which caused huge social and economic losses. Using reanalysis data, the atmospheric circulation anomalies and possible mechanisms related to the summer precipitation anomalies in 2015 were examined. The results showed that both El Niño and certain atmospheric teleconnections, including the Pacific Japan/East Asia Pacific (PJ/EAP), Eurasia pattern (EU), British–Baikal Corridor pattern (BBC), and Silk Road mode (SR), contributed to the dipole pattern of precipitation anomalies. The combination of these factors caused a southwards shift of the western Pacific subtropical high (WPSH) and a weakening of the East Asian summer monsoon. Consequently, it was difficult for the monsoon front and associated rain band to migrate northwards, which meant that less precipitation occurred in northern China while more precipitation occurred in southern China. This resulted in the SF-ND event. Moreover, further analysis revealed that global sea surface temperature anomalies (SSTAs) or sea-ice anomalies were key to stimulating these atmospheric teleconnections.
, Available online
, Manuscript accepted 15 May 2023, doi: 10.1007/s00376-023-2386-1
Abstract:
In this study, we put forward a radiative-convective-transportive energy balance model of a gray atmosphere to examine individual roles of the greenhouse effect of water vapor, vertical convection, and atmospheric poleward energy transport as well as their combined effects for a quasi-linear relationship between the outgoing longwave radiation (OLR) and surface temperature (TS). The greenhouse effect of water vapor enhances the meridional gradient of surface temperature, thereby directly contributing to a quasi-linear OLR-TS relationship. The atmospheric poleward energy transport decreases the meridional gradient of surface temperature. As a result of the poleward energy transport, tropical (high-latitude) atmosphere-surface columns emit less (more) OLR than the solar energy input at their respective locations, causing a substantial reduction of the meridional gradient of the OLR. The combined effect of reducing the meridional gradients of both OLR and surface temperature by the poleward energy transport also contributes to the quasi-linear OLR-TS relationship. Vertical convective energy transport reduces the meridional gradient of surface temperature without affecting the meridional gradient of OLR, thereby suppressing part of the reduction to the increasing rate of OLR with surface temperature by the greenhouse effect of water vapor and poleward energy transport. Because of the nature of the energy balance in the climate system, such a quasi-linear relationship is also a good approximation for the relationship between the annual-mean net downward solar energy flux at the top of the atmosphere and surface temperature.
In this study, we put forward a radiative-convective-transportive energy balance model of a gray atmosphere to examine individual roles of the greenhouse effect of water vapor, vertical convection, and atmospheric poleward energy transport as well as their combined effects for a quasi-linear relationship between the outgoing longwave radiation (OLR) and surface temperature (TS). The greenhouse effect of water vapor enhances the meridional gradient of surface temperature, thereby directly contributing to a quasi-linear OLR-TS relationship. The atmospheric poleward energy transport decreases the meridional gradient of surface temperature. As a result of the poleward energy transport, tropical (high-latitude) atmosphere-surface columns emit less (more) OLR than the solar energy input at their respective locations, causing a substantial reduction of the meridional gradient of the OLR. The combined effect of reducing the meridional gradients of both OLR and surface temperature by the poleward energy transport also contributes to the quasi-linear OLR-TS relationship. Vertical convective energy transport reduces the meridional gradient of surface temperature without affecting the meridional gradient of OLR, thereby suppressing part of the reduction to the increasing rate of OLR with surface temperature by the greenhouse effect of water vapor and poleward energy transport. Because of the nature of the energy balance in the climate system, such a quasi-linear relationship is also a good approximation for the relationship between the annual-mean net downward solar energy flux at the top of the atmosphere and surface temperature.
, Available online
, Manuscript accepted 12 May 2023, doi: 10.1007/s00376-023-2235-2
Abstract:
Dramatic changes in the sea ice characteristics in the Barents Sea have potential consequences for the weather and climate systems of mid-latitude continents, Arctic ecosystems, and fisheries, as well as Arctic maritime navigation. Simulations and projections of winter sea ice in the Barents Sea based on the latest 41 climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are investigated in this study. Results show that most CMIP6 models overestimate winter sea ice in the Barents Sea and underestimate its decreasing trend. The discrepancy is mainly attributed to the simulation bias towards an overly weak ocean heat transport through the Barents Sea Opening and the underestimation of its increasing trend. The methods of observation-based model selection and emergent constraint were used to project future winter sea ice changes in the Barents Sea. Projections indicate that sea ice in the Barents Sea will continue to decline in a warming climate and that a winter ice-free Barents Sea will occur for the first time during 2042–2089 under the Shared Socioeconomic Pathway 585 (SSP5-8.5). Even in the observation-based selected models, the sensitivity of winter sea ice in the Barents Sea to global warming is weaker than observed, indicating that a winter ice-free Barents Sea might occur earlier than projected by the CMIP6 simulations.
Dramatic changes in the sea ice characteristics in the Barents Sea have potential consequences for the weather and climate systems of mid-latitude continents, Arctic ecosystems, and fisheries, as well as Arctic maritime navigation. Simulations and projections of winter sea ice in the Barents Sea based on the latest 41 climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are investigated in this study. Results show that most CMIP6 models overestimate winter sea ice in the Barents Sea and underestimate its decreasing trend. The discrepancy is mainly attributed to the simulation bias towards an overly weak ocean heat transport through the Barents Sea Opening and the underestimation of its increasing trend. The methods of observation-based model selection and emergent constraint were used to project future winter sea ice changes in the Barents Sea. Projections indicate that sea ice in the Barents Sea will continue to decline in a warming climate and that a winter ice-free Barents Sea will occur for the first time during 2042–2089 under the Shared Socioeconomic Pathway 585 (SSP5-8.5). Even in the observation-based selected models, the sensitivity of winter sea ice in the Barents Sea to global warming is weaker than observed, indicating that a winter ice-free Barents Sea might occur earlier than projected by the CMIP6 simulations.
, Available online
, Manuscript accepted 09 May 2023, doi: 10.1007/s00376-023-3025-6
Abstract:
An extreme torrential rain (ETR) event occurred in Henan Province, China, during 18-21 July 2021. Based on hourly rain-gauge observations and ERA5 reanalysis data, the ETR was studied from the perspective of kinetic energy (K), which can be divided into rotational wind ( V R) kinetic energy (KR), divergent wind kinetic energy (KD), and the kinetic energy of the interaction between the divergent and rotational winds (KRD). According to the hourly precipitation intensity variability, the ETR process was divided into an initial stage, a rapid increase stage, and maintenance stage. Results showed that the intensification and maintenance of ETR were closely related to the upper-level K, and most closely related to the upper-level KR, with a correlation coefficient of up to 0.9. In particular, the peak value of hourly rainfall intensity lagged behind the KR by 8 h. Furthermore, diagnosis showed that K transformation from unresolvable to resolvable scales made the ETR increase slowly. The meridional rotational wind (uR) and meridional gradient of the geopotential (φ) jointly determined the conversion of available potential energy (APE) to KR through the barotropic process, which dominated the rapid enhancement of KR and then caused the rapid increase in ETR. The transportation of K by rotational wind consumed KR, and basically offset the KR produced by the barotropic process, which basically kept KR stable at a high value, thus maintaining the ETR.
An extreme torrential rain (ETR) event occurred in Henan Province, China, during 18-21 July 2021. Based on hourly rain-gauge observations and ERA5 reanalysis data, the ETR was studied from the perspective of kinetic energy (K), which can be divided into rotational wind ( V R) kinetic energy (KR), divergent wind kinetic energy (KD), and the kinetic energy of the interaction between the divergent and rotational winds (KRD). According to the hourly precipitation intensity variability, the ETR process was divided into an initial stage, a rapid increase stage, and maintenance stage. Results showed that the intensification and maintenance of ETR were closely related to the upper-level K, and most closely related to the upper-level KR, with a correlation coefficient of up to 0.9. In particular, the peak value of hourly rainfall intensity lagged behind the KR by 8 h. Furthermore, diagnosis showed that K transformation from unresolvable to resolvable scales made the ETR increase slowly. The meridional rotational wind (uR) and meridional gradient of the geopotential (φ) jointly determined the conversion of available potential energy (APE) to KR through the barotropic process, which dominated the rapid enhancement of KR and then caused the rapid increase in ETR. The transportation of K by rotational wind consumed KR, and basically offset the KR produced by the barotropic process, which basically kept KR stable at a high value, thus maintaining the ETR.
, Available online
, Manuscript accepted 06 May 2023, doi: 10.1007/s00376-023-2393-2
Abstract:
Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice, changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models’ performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario. Thereafter, it may decrease (or remain stable) if the Arctic warming crosses a threshold (or is extensively constrained).
Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice, changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models’ performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario. Thereafter, it may decrease (or remain stable) if the Arctic warming crosses a threshold (or is extensively constrained).
Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets
, Available online
, Manuscript accepted 06 May 2023, doi: 10.1007/s00376-023-3047-0
Abstract:
El Niño–Southern Oscillation (ENSO), the leading mode of global interannual variability, usually intensifies the Hadley Circulation (HC), and meanwhile constrains its meridional extension, leading to an equatorward movement of the jet system. Previous studies have investigated the response of HC to ENSO events using different reanalysis datasets and evaluated their capability in capturing the main features of ENSO-associated HC anomalies. However, these studies mainly focused on the global HC, represented by a zonal-mean mass stream function (MSF). Comparatively fewer studies have evaluated HC responses from a regional perspective, partly due to the prerequisite of the Stokes MSF, which prevents us from integrating a regional HC. In this study, we adopt a recently developed technique to construct the three-dimensional structure of HC and evaluate the capability of eight state-of-the-art reanalyses in reproducing the regional HC response to ENSO events. Results show that all eight reanalyses reproduce the spatial structure of HC responses well, with an intensified HC around the central-eastern Pacific but weakened circulations around the Indo-Pacific warm pool and tropical Atlantic. The spatial correlation coefficient of the three-dimensional HC anomalies among the different datasets is always larger than 0.93. However, these datasets may not capture the amplitudes of the HC responses well. This uncertainty is especially large for ENSO-associated equatorially asymmetric HC anomalies, with the maximum amplitude in Climate Forecast System Reanalysis (CFSR) being about 2.7 times the minimum value in the Twentieth Century Reanalysis (20CR). One should be careful when using reanalysis data to evaluate the intensity of ENSO-associated HC anomalies.
El Niño–Southern Oscillation (ENSO), the leading mode of global interannual variability, usually intensifies the Hadley Circulation (HC), and meanwhile constrains its meridional extension, leading to an equatorward movement of the jet system. Previous studies have investigated the response of HC to ENSO events using different reanalysis datasets and evaluated their capability in capturing the main features of ENSO-associated HC anomalies. However, these studies mainly focused on the global HC, represented by a zonal-mean mass stream function (MSF). Comparatively fewer studies have evaluated HC responses from a regional perspective, partly due to the prerequisite of the Stokes MSF, which prevents us from integrating a regional HC. In this study, we adopt a recently developed technique to construct the three-dimensional structure of HC and evaluate the capability of eight state-of-the-art reanalyses in reproducing the regional HC response to ENSO events. Results show that all eight reanalyses reproduce the spatial structure of HC responses well, with an intensified HC around the central-eastern Pacific but weakened circulations around the Indo-Pacific warm pool and tropical Atlantic. The spatial correlation coefficient of the three-dimensional HC anomalies among the different datasets is always larger than 0.93. However, these datasets may not capture the amplitudes of the HC responses well. This uncertainty is especially large for ENSO-associated equatorially asymmetric HC anomalies, with the maximum amplitude in Climate Forecast System Reanalysis (CFSR) being about 2.7 times the minimum value in the Twentieth Century Reanalysis (20CR). One should be careful when using reanalysis data to evaluate the intensity of ENSO-associated HC anomalies.
, Available online
, Manuscript accepted 28 April 2023, doi: 10.1007/s00376-023-2366-5
Abstract:
Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop cultivation. Increases in the frequency of these rare events in a future warmer climate would have significant societal impact. This study uses an ensemble of 10 Coupled Model Intercomparison Project (CMIP) models to investigate the projected change in agricultural flash drought during the 21st century. Comparison across geographical regions and climatic zones indicates that individual events are preceded by anomalously low relative humidity and precipitation, with long-term trends governed by changes in temperature, relative humidity, and soil moisture. As a result of these processes, the frequency of both upper-level and root-zone flash drought is projected to more than double in the mid- and high latitudes over the 21st century, with hot spots developing in the temperate regions of Europe, and humid regions of South America, Europe, and southern Africa.
Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop cultivation. Increases in the frequency of these rare events in a future warmer climate would have significant societal impact. This study uses an ensemble of 10 Coupled Model Intercomparison Project (CMIP) models to investigate the projected change in agricultural flash drought during the 21st century. Comparison across geographical regions and climatic zones indicates that individual events are preceded by anomalously low relative humidity and precipitation, with long-term trends governed by changes in temperature, relative humidity, and soil moisture. As a result of these processes, the frequency of both upper-level and root-zone flash drought is projected to more than double in the mid- and high latitudes over the 21st century, with hot spots developing in the temperate regions of Europe, and humid regions of South America, Europe, and southern Africa.
, Available online
, Manuscript accepted 24 April 2023, doi: 10.1007/s00376-023-2332-2
Abstract:
High spatiotemporal resolution radiances from the advanced imagers onboard the new generation of geostationary weather satellites provide a unique opportunity to evaluate the abilities of various reanalysis datasets to depict multilayer tropospheric water vapor (WV), thereby enhancing our understanding of the deficiencies of WV in reanalysis datasets. Based on daily measurements from the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite in 2016, the bias features of multilayer WV from six reanalysis datasets over East Asia are thoroughly evaluated. The assessments show that wet biases exist in the upper troposphere in all six reanalysis datasets; in particular, these biases are much larger in summer. Overall, we find better depictions of WV in the middle troposphere than in the upper troposphere. The accuracy of WV in the ERA5 dataset is the highest, in terms of the bias magnitude, dispersion, and pattern similarity. The characteristics of the WV bias over the Tibetan Plateau are significantly different from those over other parts of East Asia. In addition, the reanalysis datasets all capture the shift of the subtropical high very well, with ERA5 performing better overall.
High spatiotemporal resolution radiances from the advanced imagers onboard the new generation of geostationary weather satellites provide a unique opportunity to evaluate the abilities of various reanalysis datasets to depict multilayer tropospheric water vapor (WV), thereby enhancing our understanding of the deficiencies of WV in reanalysis datasets. Based on daily measurements from the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite in 2016, the bias features of multilayer WV from six reanalysis datasets over East Asia are thoroughly evaluated. The assessments show that wet biases exist in the upper troposphere in all six reanalysis datasets; in particular, these biases are much larger in summer. Overall, we find better depictions of WV in the middle troposphere than in the upper troposphere. The accuracy of WV in the ERA5 dataset is the highest, in terms of the bias magnitude, dispersion, and pattern similarity. The characteristics of the WV bias over the Tibetan Plateau are significantly different from those over other parts of East Asia. In addition, the reanalysis datasets all capture the shift of the subtropical high very well, with ERA5 performing better overall.
, Available online
, Manuscript accepted 24 April 2023, doi: 10.1007/s00376-023-2348-7
Abstract:
Heat events may be humid or dry. While several indices incorporate humidity, such combined indices obscure identification and exploration of heat events by their different humidity characteristics. The new HadISDH.extremes global gridded monitoring product uniquely provides a range of wet and dry bulb temperature extremes indices. Analysis of this new data product demonstrates its value as a tool for quantifying exposure to humid verses dry heat events. It also enables exploration into “stealth heat events”, where humidity is high, perhaps enough to affect productivity and health, while temperature remains moderate. Such events may not typically be identified as “heat events” by temperature-focused heat indices. Over 1973–2022, the peak magnitude of humid extremes (maximum daily wet bulb temperature over a month; TwX) for the global annual mean increased significantly at 0.13 ± 0.04°C (10 yr)−1, which is slightly slower than the global annual mean Tw increase of 0.22± 0.04°C (10 yr)−1. The frequency of moderate humid extreme events per year (90th percentile daily maxima wet bulb temperature exceedance; TwX90p) also increased significantly at 4.61 ± 1.07 d yr−1 (10 yr)−1. These rates were slower than for temperature extremes, TX and TX90p, which respectively increased significantly at 0.27 ± 0.04°C (10 yr)−1 and 5.53 ± 0.72 d yr−1 (10 yr)−1. Similarly, for the UK/Europe focus region, JJA-mean TwX increased significantly, again at a slower rate than for TX and mean Tw. HadISDH.extremes shows some evidence of “stealth heat events” occurring where humidity is high but temperature remains more moderate.
Heat events may be humid or dry. While several indices incorporate humidity, such combined indices obscure identification and exploration of heat events by their different humidity characteristics. The new HadISDH.extremes global gridded monitoring product uniquely provides a range of wet and dry bulb temperature extremes indices. Analysis of this new data product demonstrates its value as a tool for quantifying exposure to humid verses dry heat events. It also enables exploration into “stealth heat events”, where humidity is high, perhaps enough to affect productivity and health, while temperature remains moderate. Such events may not typically be identified as “heat events” by temperature-focused heat indices. Over 1973–2022, the peak magnitude of humid extremes (maximum daily wet bulb temperature over a month; TwX) for the global annual mean increased significantly at 0.13 ± 0.04°C (10 yr)−1, which is slightly slower than the global annual mean Tw increase of 0.22± 0.04°C (10 yr)−1. The frequency of moderate humid extreme events per year (90th percentile daily maxima wet bulb temperature exceedance; TwX90p) also increased significantly at 4.61 ± 1.07 d yr−1 (10 yr)−1. These rates were slower than for temperature extremes, TX and TX90p, which respectively increased significantly at 0.27 ± 0.04°C (10 yr)−1 and 5.53 ± 0.72 d yr−1 (10 yr)−1. Similarly, for the UK/Europe focus region, JJA-mean TwX increased significantly, again at a slower rate than for TX and mean Tw. HadISDH.extremes shows some evidence of “stealth heat events” occurring where humidity is high but temperature remains more moderate.
, Available online
, Manuscript accepted 20 April 2023, doi: 10.1007/s00376-023-2298-0
Abstract:
Nested simulations of a downslope windstorm over Cangshan mountain, Yunnan, China, have been used to demonstrate a method of topographic smoothing that preserves a relatively large amount of terrain detail compared to typical smoothing procedures required for models with terrain-following grids to run stably. The simulations were carried out using the Met Office Unified Model (MetUM) to investigate downslope winds. The smoothing method seamlessly blends two terrain datasets to which uniform smoothing has been applied − one with a minimum of smoothing, the other smoothed more heavily to remove gradients that would cause model instabilities. The latter dataset dominates the blend where the steepest slopes exist, but this is localised and recedes outside these areas. As a result, increased detail is starkly apparent in depictions of flow simulated using the blend, compared to one using the default approach. This includes qualitative flow details that were absent in the latter, such as narrow shooting flows emerging from roughly 1−2 km wide leeside channels. Flow separation is more common due to steeper lee slopes. The use of targeted smoothing also results in increased lee side temporal variability at a given point during the windstorm, including over flat areas. Low-/high-pass filtering of the wind perturbation field reveals that relative spatial variability above 30 km in scale (reflecting the background flow) is similar whether or not targeting is used. Beneath this scale, when smoothing is targeted, relative flow variability decreases at the larger scales,and increases at lower scales. This seems linked to fast smaller scale flows disturbing more coherent flows (notably an along-valley current over Erhai Lake). Spatial variability of winds in the model is unsurprisingly weaker at key times than is observed across a local network sampling mesoscale variation, but results are compromised due to relatively few observation locations sampling the windstorm. Only when targeted smoothing is applied does the model capture the downslope windstorm's extension over the city of Dali at the mountain's foot, and the peak mean absolute wind.
Nested simulations of a downslope windstorm over Cangshan mountain, Yunnan, China, have been used to demonstrate a method of topographic smoothing that preserves a relatively large amount of terrain detail compared to typical smoothing procedures required for models with terrain-following grids to run stably. The simulations were carried out using the Met Office Unified Model (MetUM) to investigate downslope winds. The smoothing method seamlessly blends two terrain datasets to which uniform smoothing has been applied − one with a minimum of smoothing, the other smoothed more heavily to remove gradients that would cause model instabilities. The latter dataset dominates the blend where the steepest slopes exist, but this is localised and recedes outside these areas. As a result, increased detail is starkly apparent in depictions of flow simulated using the blend, compared to one using the default approach. This includes qualitative flow details that were absent in the latter, such as narrow shooting flows emerging from roughly 1−2 km wide leeside channels. Flow separation is more common due to steeper lee slopes. The use of targeted smoothing also results in increased lee side temporal variability at a given point during the windstorm, including over flat areas. Low-/high-pass filtering of the wind perturbation field reveals that relative spatial variability above 30 km in scale (reflecting the background flow) is similar whether or not targeting is used. Beneath this scale, when smoothing is targeted, relative flow variability decreases at the larger scales,and increases at lower scales. This seems linked to fast smaller scale flows disturbing more coherent flows (notably an along-valley current over Erhai Lake). Spatial variability of winds in the model is unsurprisingly weaker at key times than is observed across a local network sampling mesoscale variation, but results are compromised due to relatively few observation locations sampling the windstorm. Only when targeted smoothing is applied does the model capture the downslope windstorm's extension over the city of Dali at the mountain's foot, and the peak mean absolute wind.
, Available online
, Manuscript accepted 18 April 2023, doi: 10.1007/s00376-023-3001-1
Abstract:
The application of deep learning is fast developing in climate prediction, in which El Niño–Southern Oscillation (ENSO), as the most dominant disaster-causing climate event, is a key target. Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices. The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies (SSTAs) in the equatorial Pacific by training a convolutional neural network (CNN) model with historical simulations from CMIP6 models. Compared with dynamical models, the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific, but not in the eastern Pacific. The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months. A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.
The application of deep learning is fast developing in climate prediction, in which El Niño–Southern Oscillation (ENSO), as the most dominant disaster-causing climate event, is a key target. Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices. The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies (SSTAs) in the equatorial Pacific by training a convolutional neural network (CNN) model with historical simulations from CMIP6 models. Compared with dynamical models, the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific, but not in the eastern Pacific. The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months. A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.
, Available online
, Manuscript accepted 14 April 2023, doi: 10.1007/s00376-023-2319-z
Abstract:
The frequency and duration of observed concurrent hot and dry events (HDEs) over China during the growing season (April–September) exhibit significant decadal changes across the mid-1990s. These changes are characterized by increases in HDE frequency and duration over most of China, with relatively large increases over southeastern China (SEC), northern China (NC), and northeastern China (NEC). The frequency of HDEs averaged over China in the present day (PD, 1994–2011) is double that in the early period (EP, 1964–81); the duration of HDEs increases by 60%. Climate experiments with the Met Office Unified Model (MetUM-GOML2) are used to estimate the contributions of anthropogenic forcing to HDE decadal changes over China. Anthropogenic forcing changes can explain 60%–70% of the observed decadal changes, suggesting an important anthropogenic influence on HDE changes over China across the mid-1990s. Single-forcing experiments indicate that the increase in greenhouse gas (GHG) concentrations dominates the simulated decadal changes, increasing the frequency and duration of HDEs throughout China. The change in anthropogenic aerosol (AA) emissions significantly decreases the frequency and duration of HDEs over SEC and NC, but the magnitude of the decrease is much smaller than the increase induced by GHGs. The changes in HDEs in response to anthropogenic forcing are mainly due to the response of climatological mean surface air temperatures. The contributions from changes in variability and changes in climatological mean soil moisture and evapotranspiration are relatively small. The physical processes associated with the response of HDEs to GHG and AA changes are also revealed.
The frequency and duration of observed concurrent hot and dry events (HDEs) over China during the growing season (April–September) exhibit significant decadal changes across the mid-1990s. These changes are characterized by increases in HDE frequency and duration over most of China, with relatively large increases over southeastern China (SEC), northern China (NC), and northeastern China (NEC). The frequency of HDEs averaged over China in the present day (PD, 1994–2011) is double that in the early period (EP, 1964–81); the duration of HDEs increases by 60%. Climate experiments with the Met Office Unified Model (MetUM-GOML2) are used to estimate the contributions of anthropogenic forcing to HDE decadal changes over China. Anthropogenic forcing changes can explain 60%–70% of the observed decadal changes, suggesting an important anthropogenic influence on HDE changes over China across the mid-1990s. Single-forcing experiments indicate that the increase in greenhouse gas (GHG) concentrations dominates the simulated decadal changes, increasing the frequency and duration of HDEs throughout China. The change in anthropogenic aerosol (AA) emissions significantly decreases the frequency and duration of HDEs over SEC and NC, but the magnitude of the decrease is much smaller than the increase induced by GHGs. The changes in HDEs in response to anthropogenic forcing are mainly due to the response of climatological mean surface air temperatures. The contributions from changes in variability and changes in climatological mean soil moisture and evapotranspiration are relatively small. The physical processes associated with the response of HDEs to GHG and AA changes are also revealed.
, Available online
, Manuscript accepted 12 April 2023, doi: 10.1007/s00376-023-2303-7
Abstract:
Three cases of microphysical characteristics and kinematic structures in the negative temperature region of summer mesoscale cloud systems over the eastern Tibetan Plateau (TP) were investigated using X-band dual-polarization radar. The time–height series of radar physical variables and mesoscale horizontal divergence\begin{document}$ \bar{\delta } $\end{document} ![]()
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Three cases of microphysical characteristics and kinematic structures in the negative temperature region of summer mesoscale cloud systems over the eastern Tibetan Plateau (TP) were investigated using X-band dual-polarization radar. The time–height series of radar physical variables and mesoscale horizontal divergence
, Available online
, Manuscript accepted 10 April 2023, doi: 10.1007/s00376-023-2275-7
Abstract:
Existing studies contend that latent heating (LH) will replace sensible heating (SH) to become the dominant factor affecting the development of the Tibetan Plateau vortex (TPV) after it moves off the Tibetan Plateau (TP). However, in the process of the TPV moving off the TP requires that the airmass traverse the eastern slope of the Tibetan Plateau (ESTP) where the topography and diabatic heating (DH) conditions rapidly change. How LH gradually replaces SH to become the dominant factor in the development of the TPV over the ESTP is still not very clear. In this paper, an analysis of a typical case of a TPV with a long life history over the ESTP is performed by using multi-sourced meteorological data and model simulations. The results show that SH from the TP surface can change the TPV-associated precipitation distribution by temperature advection after the TPV moves off the TP. The LH can then directly promote the development of the TPV and has a certain guiding effect on the track of the TPV. The SH can control the active area of LH by changing the falling area of the TPV-associated precipitation, so it still plays a key role in the development and tracking of the TPV even though it has moved out of the main body of the TP.
Existing studies contend that latent heating (LH) will replace sensible heating (SH) to become the dominant factor affecting the development of the Tibetan Plateau vortex (TPV) after it moves off the Tibetan Plateau (TP). However, in the process of the TPV moving off the TP requires that the airmass traverse the eastern slope of the Tibetan Plateau (ESTP) where the topography and diabatic heating (DH) conditions rapidly change. How LH gradually replaces SH to become the dominant factor in the development of the TPV over the ESTP is still not very clear. In this paper, an analysis of a typical case of a TPV with a long life history over the ESTP is performed by using multi-sourced meteorological data and model simulations. The results show that SH from the TP surface can change the TPV-associated precipitation distribution by temperature advection after the TPV moves off the TP. The LH can then directly promote the development of the TPV and has a certain guiding effect on the track of the TPV. The SH can control the active area of LH by changing the falling area of the TPV-associated precipitation, so it still plays a key role in the development and tracking of the TPV even though it has moved out of the main body of the TP.
, Available online
, Manuscript accepted 10 April 2023, doi: 10.1007/s00376-023-2329-x
Abstract:
The pan-Arctic is confronted with air pollution transported from lower latitudes. Observations have shown that aerosols help increase plant photosynthesis through the diffuse radiation fertilization effects (DRFEs). While such DRFEs have been explored at low to middle latitudes, the aerosol impacts on pan-Arctic ecosystems and the contributions by anthropogenic and natural emission sources remain less quantified. Here, we perform regional simulations at 0.2º×0.2º using a well-validated vegetation model (Yale Interactive terrestrial Biosphere, YIBs) in combination with multi-source of observations to quantify the impacts of aerosol DRFEs on the net primary productivity (NPP) in the pan-Arctic during 2001–19. Results show that aerosol DRFEs increase pan-Arctic NPP by 2.19 Pg C (12.8%) yr−1 under clear-sky conditions, in which natural and anthropogenic sources contribute to 8.9% and 3.9%, respectively. Under all-sky conditions, such DRFEs are largely dampened by cloud to only 0.26 Pg C (1.24%) yr−1, with contributions of 0.65% by natural and 0.59% by anthropogenic species. Natural aerosols cause a positive NPP trend of 0.022% yr−1 following the increased fire activities in the pan-Arctic. In contrast, anthropogenic aerosols induce a negative trend of −0.01% yr−1 due to reduced emissions from the middle latitudes. Such trends in aerosol DRFEs show a turning point in the year of 2007 with more positive NPP trends by natural aerosols but negative NPP trends by anthropogenic aerosols thereafter. Though affected by modeling uncertainties, this study suggests a likely increasing impact of aerosols on terrestrial ecosystems in the pan-Arctic under global warming.
The pan-Arctic is confronted with air pollution transported from lower latitudes. Observations have shown that aerosols help increase plant photosynthesis through the diffuse radiation fertilization effects (DRFEs). While such DRFEs have been explored at low to middle latitudes, the aerosol impacts on pan-Arctic ecosystems and the contributions by anthropogenic and natural emission sources remain less quantified. Here, we perform regional simulations at 0.2º×0.2º using a well-validated vegetation model (Yale Interactive terrestrial Biosphere, YIBs) in combination with multi-source of observations to quantify the impacts of aerosol DRFEs on the net primary productivity (NPP) in the pan-Arctic during 2001–19. Results show that aerosol DRFEs increase pan-Arctic NPP by 2.19 Pg C (12.8%) yr−1 under clear-sky conditions, in which natural and anthropogenic sources contribute to 8.9% and 3.9%, respectively. Under all-sky conditions, such DRFEs are largely dampened by cloud to only 0.26 Pg C (1.24%) yr−1, with contributions of 0.65% by natural and 0.59% by anthropogenic species. Natural aerosols cause a positive NPP trend of 0.022% yr−1 following the increased fire activities in the pan-Arctic. In contrast, anthropogenic aerosols induce a negative trend of −0.01% yr−1 due to reduced emissions from the middle latitudes. Such trends in aerosol DRFEs show a turning point in the year of 2007 with more positive NPP trends by natural aerosols but negative NPP trends by anthropogenic aerosols thereafter. Though affected by modeling uncertainties, this study suggests a likely increasing impact of aerosols on terrestrial ecosystems in the pan-Arctic under global warming.
, Available online
, Manuscript accepted 10 April 2023, doi: 10.1007/s00376-023-2313-5
Abstract:
This study explores the linkage between summertime temperature fluctuations over midlatitude Eurasia and the preceding Arctic sea ice concentration (SIC) by utilizing the squared norm of the temperature anomaly, the essential part of local eddy available potential energy, as a metric to quantify the temperature fluctuations with weather patterns on various timescales. By comparing groups of singular value decomposition (SVD) analysis, we suggest a significant linkage between strong (weak) August 10-to-30-day temperature fluctuations over mid-west Asia and enhanced (decreased) Barents-Kara Sea ice in the previous February. We find that when the February SIC increases in the Barents-Kara Sea, a zonal dipolar pattern of SST anomalies appears in the Atlantic subpolar region and lasts from February into the summer months. Evidence suggests that in such a background state, the atmospheric circulation changes evidently from July to August, so that the August is characterized by an amplified meridional circulation over Eurasia, weakened westerlies, and high-pressure anomalies along the Arctic coast. Moreover, the 10-to-30-day wave becomes more active in the North Atlantic–Barents-Kara Sea–Central Asia regions and manifests a more evident southward propagation from the Barents-Kara Sea into the Ural region, which is responsible for the enhanced 10-to-30-day wave activity and temperature fluctuations in the region.
This study explores the linkage between summertime temperature fluctuations over midlatitude Eurasia and the preceding Arctic sea ice concentration (SIC) by utilizing the squared norm of the temperature anomaly, the essential part of local eddy available potential energy, as a metric to quantify the temperature fluctuations with weather patterns on various timescales. By comparing groups of singular value decomposition (SVD) analysis, we suggest a significant linkage between strong (weak) August 10-to-30-day temperature fluctuations over mid-west Asia and enhanced (decreased) Barents-Kara Sea ice in the previous February. We find that when the February SIC increases in the Barents-Kara Sea, a zonal dipolar pattern of SST anomalies appears in the Atlantic subpolar region and lasts from February into the summer months. Evidence suggests that in such a background state, the atmospheric circulation changes evidently from July to August, so that the August is characterized by an amplified meridional circulation over Eurasia, weakened westerlies, and high-pressure anomalies along the Arctic coast. Moreover, the 10-to-30-day wave becomes more active in the North Atlantic–Barents-Kara Sea–Central Asia regions and manifests a more evident southward propagation from the Barents-Kara Sea into the Ural region, which is responsible for the enhanced 10-to-30-day wave activity and temperature fluctuations in the region.
, Available online
, Manuscript accepted 06 April 2023, doi: 10.1007/s00376-023-2320-6
Abstract:
This study evaluates the Arctic sea-ice simulation of the SODA3 dataset driven by different atmospheric forcing fields and explores the errors of the Arctic sea-ice simulation caused by the forcing field. We find that the SODA3 data driven by different forcing fields represent a significant systematical error in the simulation of Arctic sea-ice concentration, showing a low concentration of thick ice and a high concentration of thin ice. In terms of sea-ice extent, the SODA3 data from different versions well characterize the interannual variability and declining trend in the observed data, but they overestimate the overall Arctic sea-ice extent, which is related to excessive simulation of ice in the sea-ice margin. Compared to observations, all the chosen SODA3 reanalysis versions driven by different atmospheric forcing generally tend to underestimate the Arctic sea-ice thickness, especially for thick ice in the multi-year sea-ice regions. Inaccurate simulations of Arctic sea-ice transport may partly explain the error in SODA3 sea-ice thickness in multi-year sea-ice areas. The results of different SDOA3 versions differ greatly in the Beaufort Sea, the Fram Strait, and the Central Arctic Sea. The difference in sea-ice thickness among different SODA3 versions is primarily due to the thermodynamic contribution, which may come from the diversity of atmospheric forcing fields. Our work provides a reference for using SODA3 data to study Arctic sea ice.
This study evaluates the Arctic sea-ice simulation of the SODA3 dataset driven by different atmospheric forcing fields and explores the errors of the Arctic sea-ice simulation caused by the forcing field. We find that the SODA3 data driven by different forcing fields represent a significant systematical error in the simulation of Arctic sea-ice concentration, showing a low concentration of thick ice and a high concentration of thin ice. In terms of sea-ice extent, the SODA3 data from different versions well characterize the interannual variability and declining trend in the observed data, but they overestimate the overall Arctic sea-ice extent, which is related to excessive simulation of ice in the sea-ice margin. Compared to observations, all the chosen SODA3 reanalysis versions driven by different atmospheric forcing generally tend to underestimate the Arctic sea-ice thickness, especially for thick ice in the multi-year sea-ice regions. Inaccurate simulations of Arctic sea-ice transport may partly explain the error in SODA3 sea-ice thickness in multi-year sea-ice areas. The results of different SDOA3 versions differ greatly in the Beaufort Sea, the Fram Strait, and the Central Arctic Sea. The difference in sea-ice thickness among different SODA3 versions is primarily due to the thermodynamic contribution, which may come from the diversity of atmospheric forcing fields. Our work provides a reference for using SODA3 data to study Arctic sea ice.
, Available online
, Manuscript accepted 04 April 2023, doi: 10.1007/s00376-023-2388-z
Abstract:
The three-orbit constellation can comprehensively increase the spatial coverage of polar-orbiting satellites, but the polar-orbiting satellites currently in operation are only mid-morning-orbit and afternoon-orbit satellites. Fengyun-3E (FY-3E) was launched successfully on 5 July 2021 in China. As an early-morning-orbit satellite, FY-3E can help form a complete three-orbit observation system together with the mid-morning and afternoon satellites in the current mainstream operational system. In this study, we investigate the added benefit of FY-3E microwave sounding observations to the mid-morning-orbit Meteorological Operational satellite-B (MetOp-B) and afternoon-orbit Fengyun-3D (FY-3D) microwave observations in the Chinese Meteorological Administration global forecast system (CMA-GFS). The results show that the additional FY-3E microwave temperature sounder-3 (MWTS-3) and microwave humidity sounder-2 (MWHS-2) data can increase the global coverage of microwave temperature and humidity sounding data by 14.8% and 10.6%, respectively. It enables the CMA-GFS to achieve nearly 100% global coverage of microwave-sounding observations at each analysis time. Furthermore, after effective quality control and bias correction, the global biases and standard deviations of the differences between observations and model simulations are also reduced. Based on the Advanced Microwave Sounding Unit A and the Microwave Humidity Sounder onboard MetOp-B, and the MWTS-2 and MWHS-2 onboard FY-3D, adding the microwave sounding data of FY-3E can further reduce the errors of analysis results and improve the global prediction skills of CMA-GFS, especially for the southern-hemisphere forecasts within 96 hours, all of which are significant at the 95% confidence level.
The three-orbit constellation can comprehensively increase the spatial coverage of polar-orbiting satellites, but the polar-orbiting satellites currently in operation are only mid-morning-orbit and afternoon-orbit satellites. Fengyun-3E (FY-3E) was launched successfully on 5 July 2021 in China. As an early-morning-orbit satellite, FY-3E can help form a complete three-orbit observation system together with the mid-morning and afternoon satellites in the current mainstream operational system. In this study, we investigate the added benefit of FY-3E microwave sounding observations to the mid-morning-orbit Meteorological Operational satellite-B (MetOp-B) and afternoon-orbit Fengyun-3D (FY-3D) microwave observations in the Chinese Meteorological Administration global forecast system (CMA-GFS). The results show that the additional FY-3E microwave temperature sounder-3 (MWTS-3) and microwave humidity sounder-2 (MWHS-2) data can increase the global coverage of microwave temperature and humidity sounding data by 14.8% and 10.6%, respectively. It enables the CMA-GFS to achieve nearly 100% global coverage of microwave-sounding observations at each analysis time. Furthermore, after effective quality control and bias correction, the global biases and standard deviations of the differences between observations and model simulations are also reduced. Based on the Advanced Microwave Sounding Unit A and the Microwave Humidity Sounder onboard MetOp-B, and the MWTS-2 and MWHS-2 onboard FY-3D, adding the microwave sounding data of FY-3E can further reduce the errors of analysis results and improve the global prediction skills of CMA-GFS, especially for the southern-hemisphere forecasts within 96 hours, all of which are significant at the 95% confidence level.
, Available online
, Manuscript accepted 04 April 2023, doi: 10.1007/s00376-023-2357-6
Abstract:
The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds. Accurately obtaining the entrainment rate (λ) is particularly important for its parameterization within the overall cumulus parameterization scheme. In this study, an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculate λ of cumulus clouds in a large-eddy simulation. The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method, because λ, as calculated from the improved method, falls within the range of λ values obtained from the traditional method using different conserved variables. The probability density functions of λ for all data, different times, and different heights can be well-fitted by a log-normal distribution, which supports the assumed stochastic entrainment process in previous studies. Further analysis demonstrate that the relationship between λ and the vertical velocity is better than other thermodynamic/dynamical properties; thus, the vertical velocity is recommended as the primary influencing factor for the parameterization of λ in the future. The results of this study enhance the theoretical understanding of λ and its influencing factors and shed new light on the development of λ parameterization.
The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds. Accurately obtaining the entrainment rate (λ) is particularly important for its parameterization within the overall cumulus parameterization scheme. In this study, an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculate λ of cumulus clouds in a large-eddy simulation. The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method, because λ, as calculated from the improved method, falls within the range of λ values obtained from the traditional method using different conserved variables. The probability density functions of λ for all data, different times, and different heights can be well-fitted by a log-normal distribution, which supports the assumed stochastic entrainment process in previous studies. Further analysis demonstrate that the relationship between λ and the vertical velocity is better than other thermodynamic/dynamical properties; thus, the vertical velocity is recommended as the primary influencing factor for the parameterization of λ in the future. The results of this study enhance the theoretical understanding of λ and its influencing factors and shed new light on the development of λ parameterization.
, Available online
, Manuscript accepted 04 April 2023, doi: 10.1007/s00376-023-2294-4
Abstract:
This paper provides a systematic evaluation of the ability of 12 Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the spatial inhomogeneity of the atmospheric carbon dioxide (CO2) concentration. The multi-model ensemble mean (MME) can reasonably simulate the increasing trend of CO2 concentration from 1850 to 2014, compared with the observation data from the Scripps CO2 Program and CMIP6 prescribed data, and improves upon the CMIP5 MME CO2 concentration (which is overestimated after 1950). The growth rate of CO2 concentration in the northern hemisphere (NH) is higher than that in the southern hemisphere (SH), with the highest growth rate in the mid-latitudes of the NH. The MME can also reasonably simulate the seasonal amplitude of CO2 concentration, which is larger in the NH than in the SH and grows in amplitude after the 1950s (especially in the NH). Although the results of the MME are reasonable, there is a large spread among ESMs, and the difference between the ESMs increases with time. The MME results show that regions with relatively large CO2 concentrations (such as northern Russia, eastern China, Southeast Asia, the eastern United States, northern South America, and southern Africa) have greater seasonal variability and also exhibit a larger inter-model spread. Compared with CMIP5, the CMIP6 MME simulates an average spatial distribution of CO2 concentration that is much closer to the site observations, but the CMIP6-inter-model spread is larger. The inter-model differences of the annual means and seasonal cycles of atmospheric CO2 concentration are both attributed to the differences in natural sources and sinks of CO2 between the simulations.
This paper provides a systematic evaluation of the ability of 12 Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the spatial inhomogeneity of the atmospheric carbon dioxide (CO2) concentration. The multi-model ensemble mean (MME) can reasonably simulate the increasing trend of CO2 concentration from 1850 to 2014, compared with the observation data from the Scripps CO2 Program and CMIP6 prescribed data, and improves upon the CMIP5 MME CO2 concentration (which is overestimated after 1950). The growth rate of CO2 concentration in the northern hemisphere (NH) is higher than that in the southern hemisphere (SH), with the highest growth rate in the mid-latitudes of the NH. The MME can also reasonably simulate the seasonal amplitude of CO2 concentration, which is larger in the NH than in the SH and grows in amplitude after the 1950s (especially in the NH). Although the results of the MME are reasonable, there is a large spread among ESMs, and the difference between the ESMs increases with time. The MME results show that regions with relatively large CO2 concentrations (such as northern Russia, eastern China, Southeast Asia, the eastern United States, northern South America, and southern Africa) have greater seasonal variability and also exhibit a larger inter-model spread. Compared with CMIP5, the CMIP6 MME simulates an average spatial distribution of CO2 concentration that is much closer to the site observations, but the CMIP6-inter-model spread is larger. The inter-model differences of the annual means and seasonal cycles of atmospheric CO2 concentration are both attributed to the differences in natural sources and sinks of CO2 between the simulations.
, Available online
, Manuscript accepted 28 March 2023, doi: 10.1007/s00376-023-3011-z
Abstract:
By using the multi-taper method (MTM) of singular value decomposition (SVD), this study investigates the interdecadal evolution (10- to 30-year cycle) of precipitation over eastern China from 1951 to 2015 and its relationship with the North Pacific sea surface temperature (SST). Two significant interdecadal signals, one with an 11-year cycle and the other with a 23-year cycle, are identified in both the precipitation and SST fields. Results show that the North Pacific SST forcing modulates the precipitation distribution over China through the effects of the Pacific Decadal Oscillation (PDO)-related anomalous Aleutian low on the western Pacific subtropical high (WPSH) and Mongolia high (MH). During the development stage of the PDO cold phase associated with the 11-year cycle, a weakened WPSH and MH increased the precipitation over the Yangtze River Basin, whereas an intensified WPSH and MH caused the enhanced rain band to move northward to North China during the decay stage. During the development stage of the PDO cold phase associated with the 23-year cycle, a weakened WPSH and MH increased the precipitation over North China, whereas an intensified WPSH and the weakened MH increased the precipitation over South China during the decay stage. The 11-year and 23-year variabilities contribute differently to the precipitation variations in the different regions of China, as seen in the 1998 flooding case. The 11-year cycle mainly accounts for precipitation increases over the Yangtze River Basin, while the 23-year cycle is responsible for the precipitation increase over Northeast China. These results have important implications for understanding how the PDO modulates the precipitation distribution over China, helping to improve interdecadal climate prediction.
By using the multi-taper method (MTM) of singular value decomposition (SVD), this study investigates the interdecadal evolution (10- to 30-year cycle) of precipitation over eastern China from 1951 to 2015 and its relationship with the North Pacific sea surface temperature (SST). Two significant interdecadal signals, one with an 11-year cycle and the other with a 23-year cycle, are identified in both the precipitation and SST fields. Results show that the North Pacific SST forcing modulates the precipitation distribution over China through the effects of the Pacific Decadal Oscillation (PDO)-related anomalous Aleutian low on the western Pacific subtropical high (WPSH) and Mongolia high (MH). During the development stage of the PDO cold phase associated with the 11-year cycle, a weakened WPSH and MH increased the precipitation over the Yangtze River Basin, whereas an intensified WPSH and MH caused the enhanced rain band to move northward to North China during the decay stage. During the development stage of the PDO cold phase associated with the 23-year cycle, a weakened WPSH and MH increased the precipitation over North China, whereas an intensified WPSH and the weakened MH increased the precipitation over South China during the decay stage. The 11-year and 23-year variabilities contribute differently to the precipitation variations in the different regions of China, as seen in the 1998 flooding case. The 11-year cycle mainly accounts for precipitation increases over the Yangtze River Basin, while the 23-year cycle is responsible for the precipitation increase over Northeast China. These results have important implications for understanding how the PDO modulates the precipitation distribution over China, helping to improve interdecadal climate prediction.
, Available online
, Manuscript accepted 28 February 2023, doi: 10.1007/s00376-023-2302-8
Abstract:
Climate change is expected to have long-term impacts on drought and wildfire risks in Oregon as summers continue to become warmer and drier. This paper investigates the projected changes in drought characteristics and drought propagation in the Umatilla River Basin in northeastern Oregon for mid-century (2030–2059) and late-century (2070–2099) climate scenarios. Drought characteristics for projected climates were determined using downscaled CMIP5 climate datasets from ten climate models and Soil and Water Assessment Tool to simulate effects on hydrologic processes. Short-term (three months) drought characteristics (frequency, duration, and severity) were analyzed using four drought indices, including the Standardized Precipitation Index (SPI-3), Standardized Precipitation-Evapotranspiration Index (SPEI-3), Standardized Streamflow Index (SSI-3), and the Standardized Soil Moisture Index (SSMI-3). Results indicate that short-term meteorological droughts are projected to become more prevalent, with up to a 20% increase in the frequency of SPI-3 drought events. Short-term hydrological droughts are projected to become more frequent (average increase of 11% in frequency of SSI-3 drought events), more severe, and longer in duration (average increase of 8% for short-term droughts). Similarly, short-term agricultural droughts are projected to become more frequent (average increase of 28% in frequency of SSMI-3 drought events) but slightly shorter in duration (average decrease of 4%) in the future. Historically, drought propagation time from meteorological to hydrological drought is shorter than from meteorological to agricultural drought in most sub-basins. For the projected climate scenarios, the decrease in drought propagation time will likely stress the timing and capacity of water supply in the basin for irrigation and other uses.
Climate change is expected to have long-term impacts on drought and wildfire risks in Oregon as summers continue to become warmer and drier. This paper investigates the projected changes in drought characteristics and drought propagation in the Umatilla River Basin in northeastern Oregon for mid-century (2030–2059) and late-century (2070–2099) climate scenarios. Drought characteristics for projected climates were determined using downscaled CMIP5 climate datasets from ten climate models and Soil and Water Assessment Tool to simulate effects on hydrologic processes. Short-term (three months) drought characteristics (frequency, duration, and severity) were analyzed using four drought indices, including the Standardized Precipitation Index (SPI-3), Standardized Precipitation-Evapotranspiration Index (SPEI-3), Standardized Streamflow Index (SSI-3), and the Standardized Soil Moisture Index (SSMI-3). Results indicate that short-term meteorological droughts are projected to become more prevalent, with up to a 20% increase in the frequency of SPI-3 drought events. Short-term hydrological droughts are projected to become more frequent (average increase of 11% in frequency of SSI-3 drought events), more severe, and longer in duration (average increase of 8% for short-term droughts). Similarly, short-term agricultural droughts are projected to become more frequent (average increase of 28% in frequency of SSMI-3 drought events) but slightly shorter in duration (average decrease of 4%) in the future. Historically, drought propagation time from meteorological to hydrological drought is shorter than from meteorological to agricultural drought in most sub-basins. For the projected climate scenarios, the decrease in drought propagation time will likely stress the timing and capacity of water supply in the basin for irrigation and other uses.
, Available online
, Manuscript accepted 24 February 2023, doi: 10.1007/s00376-023-2251-2
Abstract:
Variability in the East Asian summer monsoon (EASM) brings the risk of heavy flooding or drought to the Yangtze River basin, with potentially devastating impacts. Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers, supporting livelihoods and major economic and population centres across eastern China. This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November, and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months. The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring, although the skill in June–July–August is much weaker and not consistently significant. However, there is some evidence for enhanced skill following El Niño events. The potential for decadal-scale variability in forecast skill is also examined, although we find no evidence for significant variation.
Variability in the East Asian summer monsoon (EASM) brings the risk of heavy flooding or drought to the Yangtze River basin, with potentially devastating impacts. Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers, supporting livelihoods and major economic and population centres across eastern China. This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November, and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months. The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring, although the skill in June–July–August is much weaker and not consistently significant. However, there is some evidence for enhanced skill following El Niño events. The potential for decadal-scale variability in forecast skill is also examined, although we find no evidence for significant variation.
, Available online
, Manuscript accepted 20 February 2023, doi: 10.1007/s00376-023-2338-9
Abstract:
A robust phenomenon termed the Arctic Amplification (AA) refers to the stronger warming taking place over the Arctic compared to the global mean. The AA can be confirmed through observations and reproduced in climate model simulations and shows significant seasonality and inter-model spread. This study focuses on the influence of surface type on the seasonality of AA and its inter-model spread by dividing the Arctic region into four surface types: ice-covered, ice-retreat, ice-free, and land. The magnitude and inter-model spread of Arctic surface warming are calculated from the difference between the abrupt-4 × CO2 and pre-industrial experiments of 17 CMIP6 models. The change of effective thermal inertia (ETI) in response to the quadrupling of CO2 forcing is the leading mechanism for the seasonal energy transfer mechanism, which acts to store heat temporarily in summer and then release it in winter. The ETI change is strongest over the ice-retreat region, which is also responsible for the strongest AA among the four surface types. The lack of ETI change explains the nearly uniform warming pattern across seasons over the ice-free (ocean) region. Compared to other regions, the ice-covered region shows the maximum inter-model spread in JFM, resulting from a stronger inter-model spread in the oceanic heat storage term. However, the weaker upward surface turbulent sensible and latent heat fluxes tend to suppress the inter-model spread. The relatively small inter-model spread during summer is caused by the cancellation of the inter-model spread in ice-albedo feedback with that in the oceanic heat storage term.
A robust phenomenon termed the Arctic Amplification (AA) refers to the stronger warming taking place over the Arctic compared to the global mean. The AA can be confirmed through observations and reproduced in climate model simulations and shows significant seasonality and inter-model spread. This study focuses on the influence of surface type on the seasonality of AA and its inter-model spread by dividing the Arctic region into four surface types: ice-covered, ice-retreat, ice-free, and land. The magnitude and inter-model spread of Arctic surface warming are calculated from the difference between the abrupt-4 × CO2 and pre-industrial experiments of 17 CMIP6 models. The change of effective thermal inertia (ETI) in response to the quadrupling of CO2 forcing is the leading mechanism for the seasonal energy transfer mechanism, which acts to store heat temporarily in summer and then release it in winter. The ETI change is strongest over the ice-retreat region, which is also responsible for the strongest AA among the four surface types. The lack of ETI change explains the nearly uniform warming pattern across seasons over the ice-free (ocean) region. Compared to other regions, the ice-covered region shows the maximum inter-model spread in JFM, resulting from a stronger inter-model spread in the oceanic heat storage term. However, the weaker upward surface turbulent sensible and latent heat fluxes tend to suppress the inter-model spread. The relatively small inter-model spread during summer is caused by the cancellation of the inter-model spread in ice-albedo feedback with that in the oceanic heat storage term.
, Available online
, Manuscript accepted 20 February 2023, doi: 10.1007/s00376-023-2272-x
Abstract:
Recent research has shown that snow cover induces extreme wintertime cooling and has detrimental impacts. Although the dramatic loss of Arctic sea ice certainly has contributed to a more extreme climate, the mechanism connecting sea-ice loss to extensive snow cover is still up for debate. In this study, a significant relationship between sea ice concentration (SIC) in the Barents-Kara (B-K) seas in November and snow cover extent over Eurasia in winter (November–January) has been found based in observational datasets and through numerical experiments. The reduction in B-K sea ice gives rise to a negative phase of Arctic Oscillation (AO), a deepened East Asia trough, and a shallow trough over Europe. These circulation anomalies lead to colder-than-normal Eurasian mid-latitude temperatures, providing favorable conditions for snowfall. In addition, two prominent cyclonic anomalies near Europe and Lake Baikal affect moisture transport and its divergence, which results in increased precipitation due to moisture advection and wind convergence. Furthermore, anomalous E-P flux shows that amplified upward propagating waves associated with the low SIC could contribute to the weakening of the polar vortex and southward breakouts of cold air. This work may be helpful for further understanding and predicting the snowfall conditions in the middle latitudes.
Recent research has shown that snow cover induces extreme wintertime cooling and has detrimental impacts. Although the dramatic loss of Arctic sea ice certainly has contributed to a more extreme climate, the mechanism connecting sea-ice loss to extensive snow cover is still up for debate. In this study, a significant relationship between sea ice concentration (SIC) in the Barents-Kara (B-K) seas in November and snow cover extent over Eurasia in winter (November–January) has been found based in observational datasets and through numerical experiments. The reduction in B-K sea ice gives rise to a negative phase of Arctic Oscillation (AO), a deepened East Asia trough, and a shallow trough over Europe. These circulation anomalies lead to colder-than-normal Eurasian mid-latitude temperatures, providing favorable conditions for snowfall. In addition, two prominent cyclonic anomalies near Europe and Lake Baikal affect moisture transport and its divergence, which results in increased precipitation due to moisture advection and wind convergence. Furthermore, anomalous E-P flux shows that amplified upward propagating waves associated with the low SIC could contribute to the weakening of the polar vortex and southward breakouts of cold air. This work may be helpful for further understanding and predicting the snowfall conditions in the middle latitudes.
, Available online
, Manuscript accepted 17 February 2023, doi: 10.1007/s00376-023-2297-1
Abstract:
The East Asian Summer Monsoon (EASM) provides the majority of annual rainfall to countries in East Asia. Although state-of-the-art models broadly project increased EASM rainfall, the spread of projections is large and simulations of present-day rainfall show significant climatological biases. Systematic evapotranspiration biases occur locally over East Asia, and globally over land, in simulations both with and without a coupled ocean. This study explores the relationship between evapotranspiration and EASM precipitation biases. First, idealized model simulations are presented in which the parameterization of land evaporation is modified, while sea surface temperature is fixed. The results suggest a feedback whereby excessive evapotranspiration over East Asia results in cooling of land, a weakened monsoon low, and a shift of rainfall from the Philippine Sea to China, further fueling evapotranspiration. Cross-model regressions against evapotranspiration over China indicate a similar pattern of behavior in Atmospheric Model Intercomparison Project (AMIP) simulations. Possible causes of this pattern are investigated. The feedback is not explained by an overly intense global hydrological cycle or by differences in radiative processes. Analysis of land-only simulations indicates that evapotranspiration biases are present even when models are forced with prescribed rainfall. These are strengthened when coupled to the atmosphere, suggesting a role for land-model errors in driving atmospheric biases. Coupled atmosphere–ocean models are shown to have similar evapotranspiration biases to those in AMIP over China, but different precipitation biases, including a northward shift in the ITCZ over the Pacific and Atlantic Oceans.
The East Asian Summer Monsoon (EASM) provides the majority of annual rainfall to countries in East Asia. Although state-of-the-art models broadly project increased EASM rainfall, the spread of projections is large and simulations of present-day rainfall show significant climatological biases. Systematic evapotranspiration biases occur locally over East Asia, and globally over land, in simulations both with and without a coupled ocean. This study explores the relationship between evapotranspiration and EASM precipitation biases. First, idealized model simulations are presented in which the parameterization of land evaporation is modified, while sea surface temperature is fixed. The results suggest a feedback whereby excessive evapotranspiration over East Asia results in cooling of land, a weakened monsoon low, and a shift of rainfall from the Philippine Sea to China, further fueling evapotranspiration. Cross-model regressions against evapotranspiration over China indicate a similar pattern of behavior in Atmospheric Model Intercomparison Project (AMIP) simulations. Possible causes of this pattern are investigated. The feedback is not explained by an overly intense global hydrological cycle or by differences in radiative processes. Analysis of land-only simulations indicates that evapotranspiration biases are present even when models are forced with prescribed rainfall. These are strengthened when coupled to the atmosphere, suggesting a role for land-model errors in driving atmospheric biases. Coupled atmosphere–ocean models are shown to have similar evapotranspiration biases to those in AMIP over China, but different precipitation biases, including a northward shift in the ITCZ over the Pacific and Atlantic Oceans.
, Available online
, Manuscript accepted 09 February 2023, doi: 10.1007/s00376-023-2188-5
Abstract:
The global wave model WAVEWATCH III® works well in open water. To simulate the propagation and attenuation of waves through ice-covered water, existing simulations have considered the influence of sea ice by adding the sea ice concentration in the wind wave module; however, they simply suppose that the wind cannot penetrate the ice layer and ignore the possibility of wind forcing waves below the ice cover. To improve the simulation performance of wind wave modules in the marginal ice zone (MIZ), this study proposes a parameterization scheme by directly including the sea ice thickness. Instead of scaling the wind input with the fraction of open water, this new scheme allows partial wind input in ice-covered areas based on the ice thickness. Compared with observations in the Barents Sea in 2016, the new scheme appears to improve the modeled waves in the high-frequency band. Sensitivity experiments with and without wind wave modules show that wind waves can play an important role in areas with low sea ice concentration in the MIZ.
The global wave model WAVEWATCH III® works well in open water. To simulate the propagation and attenuation of waves through ice-covered water, existing simulations have considered the influence of sea ice by adding the sea ice concentration in the wind wave module; however, they simply suppose that the wind cannot penetrate the ice layer and ignore the possibility of wind forcing waves below the ice cover. To improve the simulation performance of wind wave modules in the marginal ice zone (MIZ), this study proposes a parameterization scheme by directly including the sea ice thickness. Instead of scaling the wind input with the fraction of open water, this new scheme allows partial wind input in ice-covered areas based on the ice thickness. Compared with observations in the Barents Sea in 2016, the new scheme appears to improve the modeled waves in the high-frequency band. Sensitivity experiments with and without wind wave modules show that wind waves can play an important role in areas with low sea ice concentration in the MIZ.
, Available online
, Manuscript accepted 06 February 2023, doi: 10.1007/s00376-023-2255-y
Abstract:
Arctic changes influence not only temperature and precipitation in the midlatitudes but also contribute to severe convection. This study investigates an extreme gale event that occurred on 30 April 2021 in East China and was forced by an Arctic potential vorticity (PV) anomaly intrusion. Temperature advection steered by storms contributed to the equatorward propagation of Arctic high PV, forming the Northeast China cold vortex (NCCV). At the upper levels, a PV southward intrusion guided the combination of the polar jet and the subtropical jet, providing strong vertical wind shear and downward momentum transportation to the event. The PV anomaly cooled the upper troposphere and the northern part of East China, whereas the lower levels over southern East China were dominated by local warm air, thus establishing strong instability and baroclinicity. In addition, the entrainment of Arctic dry air strengthened the surface pressure gradient by evaporation cooling. Capturing the above mechanism has the potential to improve convective weather forecasts under climate change. This study suggests that the more frequent NCCV-induced gale events in recent years are partly due to high-latitude waviness and storm activities, and this hypothesis needs to be investigated using more cases.
Arctic changes influence not only temperature and precipitation in the midlatitudes but also contribute to severe convection. This study investigates an extreme gale event that occurred on 30 April 2021 in East China and was forced by an Arctic potential vorticity (PV) anomaly intrusion. Temperature advection steered by storms contributed to the equatorward propagation of Arctic high PV, forming the Northeast China cold vortex (NCCV). At the upper levels, a PV southward intrusion guided the combination of the polar jet and the subtropical jet, providing strong vertical wind shear and downward momentum transportation to the event. The PV anomaly cooled the upper troposphere and the northern part of East China, whereas the lower levels over southern East China were dominated by local warm air, thus establishing strong instability and baroclinicity. In addition, the entrainment of Arctic dry air strengthened the surface pressure gradient by evaporation cooling. Capturing the above mechanism has the potential to improve convective weather forecasts under climate change. This study suggests that the more frequent NCCV-induced gale events in recent years are partly due to high-latitude waviness and storm activities, and this hypothesis needs to be investigated using more cases.
, Available online
, Manuscript accepted 02 February 2023, doi: 10.1007/s00376-023-2227-2
Abstract:
Arctic sea ice loss and the associated enhanced warming has been related to midlatitude weather and climate changes through modulate meridional temperature gradients linked to circulation. However, contrasting lines of evidence result in low confidence in the influence of Arctic warming on midlatitude climate. This study examines the additional perspectives that palaeoclimate evidence provides on the decadal relationship between autumn sea ice extent (SIE) in the Barents–Kara (B–K) Seas and extreme cold wave events (ECWEs) in southern China. Reconstruction of the winter Cold Index and SIE in the B–K Seas from 1289 to 2017 shows that a significant anti-phase relationship occurred during most periods of decreasing SIE, indicating that cold winters are more likely in low SIE years due to the “bridge” role of the North Atlantic Oscillation and Siberian High. It is confirmed that the recent increase in ECWEs in southern China is closely related to the sea ice decline in the B–K Seas. However, our results show that the linkage is unstable, especially in high SIE periods, and it is probably modulated by atmospheric internal variability.
Arctic sea ice loss and the associated enhanced warming has been related to midlatitude weather and climate changes through modulate meridional temperature gradients linked to circulation. However, contrasting lines of evidence result in low confidence in the influence of Arctic warming on midlatitude climate. This study examines the additional perspectives that palaeoclimate evidence provides on the decadal relationship between autumn sea ice extent (SIE) in the Barents–Kara (B–K) Seas and extreme cold wave events (ECWEs) in southern China. Reconstruction of the winter Cold Index and SIE in the B–K Seas from 1289 to 2017 shows that a significant anti-phase relationship occurred during most periods of decreasing SIE, indicating that cold winters are more likely in low SIE years due to the “bridge” role of the North Atlantic Oscillation and Siberian High. It is confirmed that the recent increase in ECWEs in southern China is closely related to the sea ice decline in the B–K Seas. However, our results show that the linkage is unstable, especially in high SIE periods, and it is probably modulated by atmospheric internal variability.
, Available online
, Manuscript accepted 31 January 2023, doi: 10.1007/s00376-023-2258-8
Abstract:
The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon (EAWM), as well as the associated atmospheric circulation, was investigated using the hindcast data from Global Seasonal Forecast System version 5 (GloSea5), with a focus on the evolution of model bias among different forecast lead times. While GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well, systematic biases exist, including a cold bias for most of China’s mainland, especially for North and Northeast China. GloSea5 shows robust skill in predicting the EAWM intensity index two months ahead, which can be attributed to the performance in representing the leading modes of surface air temperature and associated background circulation. GloSea5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation (AO) on the EAWM, especially for the western North Pacific anticyclone (WNPAC). Compared with the North Pacific and North America, the representation of circulation anomalies over Eurasia is poor, especially for sea level pressure (SLP), which limits the prediction skill for surface air temperature over East Asia. The representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.
The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon (EAWM), as well as the associated atmospheric circulation, was investigated using the hindcast data from Global Seasonal Forecast System version 5 (GloSea5), with a focus on the evolution of model bias among different forecast lead times. While GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well, systematic biases exist, including a cold bias for most of China’s mainland, especially for North and Northeast China. GloSea5 shows robust skill in predicting the EAWM intensity index two months ahead, which can be attributed to the performance in representing the leading modes of surface air temperature and associated background circulation. GloSea5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation (AO) on the EAWM, especially for the western North Pacific anticyclone (WNPAC). Compared with the North Pacific and North America, the representation of circulation anomalies over Eurasia is poor, especially for sea level pressure (SLP), which limits the prediction skill for surface air temperature over East Asia. The representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.
, Available online
, Manuscript accepted 28 January 2023, doi: 10.1007/s00376-023-2278-4
Abstract:
Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However, reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6 (CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed. While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33% (with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration (PET) by ~32% (17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50% (29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation (water deficit) associated with dryland droughts is overestimated by 28% (24%) compared to observations. The observed increasing trends in drought fractional area, occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s, especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.
Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However, reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6 (CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed. While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33% (with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration (PET) by ~32% (17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50% (29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation (water deficit) associated with dryland droughts is overestimated by 28% (24%) compared to observations. The observed increasing trends in drought fractional area, occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s, especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.
, Available online
, Manuscript accepted 28 January 2023, doi: 10.1007/s00376-023-2288-2
Abstract:
The dynamical prediction of the Asian-Australian monsoon (AAM) has been an important and long-standing issue in climate science. In this study, the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide. Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences, especially for the second mode. The first AAM mode, from various seasonal sequences, coincides with the El Niño phase transition in the eastern-central Pacific. The second mode, initialized from boreal summer and autumn, leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring. Our findings hint that ENSO, as an early signal, is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes. Still, the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features. The multimodel ensemble (MME) mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features. The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes. The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.
The dynamical prediction of the Asian-Australian monsoon (AAM) has been an important and long-standing issue in climate science. In this study, the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide. Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences, especially for the second mode. The first AAM mode, from various seasonal sequences, coincides with the El Niño phase transition in the eastern-central Pacific. The second mode, initialized from boreal summer and autumn, leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring. Our findings hint that ENSO, as an early signal, is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes. Still, the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features. The multimodel ensemble (MME) mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features. The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes. The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.
, Available online
, Manuscript accepted 23 December 2022, doi: 10.1007/s00376-022-2216-x
Abstract:
As an important factor that directly affects agricultural production, the social economy, and policy implementation, observed changes in dry/wet conditions have become a matter of widespread concern. However, previous research has mainly focused on the long-term linear changes of dry/wet conditions, while the detection and evolution of the non-linear trends related to dry/wet changes have received less attention. The non-linear trends of the annual aridity index, obtained by the Ensemble Empirical Mode Decomposition (EEMD) method, reveal that changes in dry/wet conditions in China are asymmetric and can be characterized by contrasting features in both time and space in China. Spatially, most areas in western China have experienced transitions from drying to wetting, while opposite changes have occurred in most areas of eastern China. Temporally, the transitions occurred earlier in western China compared to eastern China. Research into the asymmetric spatial characteristics of dry/wet conditions compensates for the inadequacies of previous studies, which focused solely on temporal evolution; at the same time, it remedies the inadequacies of traditional research on linear trends over centennial timescales. Analyzing the non-linear trend also provides for a more comprehensive understanding of the drying/wetting changes in China.
As an important factor that directly affects agricultural production, the social economy, and policy implementation, observed changes in dry/wet conditions have become a matter of widespread concern. However, previous research has mainly focused on the long-term linear changes of dry/wet conditions, while the detection and evolution of the non-linear trends related to dry/wet changes have received less attention. The non-linear trends of the annual aridity index, obtained by the Ensemble Empirical Mode Decomposition (EEMD) method, reveal that changes in dry/wet conditions in China are asymmetric and can be characterized by contrasting features in both time and space in China. Spatially, most areas in western China have experienced transitions from drying to wetting, while opposite changes have occurred in most areas of eastern China. Temporally, the transitions occurred earlier in western China compared to eastern China. Research into the asymmetric spatial characteristics of dry/wet conditions compensates for the inadequacies of previous studies, which focused solely on temporal evolution; at the same time, it remedies the inadequacies of traditional research on linear trends over centennial timescales. Analyzing the non-linear trend also provides for a more comprehensive understanding of the drying/wetting changes in China.
, Available online
, Manuscript accepted 29 November 2022, doi: 10.1007/s00376-022-2201-4
Abstract:
An enhanced Warm Arctic–Cold Eurasia (WACE) pattern has been a notable feature in recent winters of the Northern Hemisphere. However, divergent results between model and observational studies of the WACE still remain. This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the WACE pattern in winter of 1980–2014 and explores the key factors causing the differences in the simulation capability among the models. The results show that the multimodel ensemble (MME) can better simulate the spatial distribution of the WACE pattern than most single models. Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well, especially the latter, usually can/cannot simulate the WACE pattern well. This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea–Kara seas (BKS) region. Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking (UB), which can transport heat to the BKS region, causing the warm Arctic, and strengthen the westerly trough downstream, cooling central Eurasia. Therefore, simulation of UB is key and significantly affects the model’s performance in simulating the WACE.
An enhanced Warm Arctic–Cold Eurasia (WACE) pattern has been a notable feature in recent winters of the Northern Hemisphere. However, divergent results between model and observational studies of the WACE still remain. This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the WACE pattern in winter of 1980–2014 and explores the key factors causing the differences in the simulation capability among the models. The results show that the multimodel ensemble (MME) can better simulate the spatial distribution of the WACE pattern than most single models. Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well, especially the latter, usually can/cannot simulate the WACE pattern well. This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea–Kara seas (BKS) region. Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking (UB), which can transport heat to the BKS region, causing the warm Arctic, and strengthen the westerly trough downstream, cooling central Eurasia. Therefore, simulation of UB is key and significantly affects the model’s performance in simulating the WACE.
, Available online
, Manuscript accepted 19 October 2022, doi: 10.1007/s00376-022-2176-1
Abstract:
In recent decades, Arctic summer sea ice extent (SIE) has shown a rapid decline overlaid with large interannual variations, both of which are influenced by geopotential height anomalies over Greenland (GL-high) and the central Arctic (CA-high). In this study, SIE along coastal Siberia (Sib-SIE) and Alaska (Ala-SIE) is found to account for about 65% and 21% of the Arctic SIE interannual variability, respectively. Variability in Ala-SIE is related to the GL-high, whereas variability in Sib-SIE is related to the CA-high. A decreased Ala-SIE is associated with decreased cloud cover and increased easterly winds along the Alaskan coast, promoting ice–albedo feedback. A decreased Sib-SIE is associated with a significant increase in water vapor and downward longwave radiation (DLR) along the Siberian coast. The years 2012 and 2020 with minimum recorded ASIE are used as examples. Compared to climatology, summer 2012 is characterized by a significantly enhanced GL-high with major sea ice loss along the Alaskan coast, while summer 2020 is characterized by an enhanced CA-high with sea ice loss focused along the Siberian coast. In 2012, the lack of cloud cover along the Alaskan coast contributed to an increase in incoming solar radiation, amplifying ice–albedo feedback there; while in 2020, the opposite occurs with an increase in cloud cover along the Alaskan coast, resulting in a slight increase in sea ice there. Along the Siberian coast, increased DLR in 2020 plays a dominant role in sea ice loss, and increased cloud cover and water vapor both contribute to the increased DLR.
In recent decades, Arctic summer sea ice extent (SIE) has shown a rapid decline overlaid with large interannual variations, both of which are influenced by geopotential height anomalies over Greenland (GL-high) and the central Arctic (CA-high). In this study, SIE along coastal Siberia (Sib-SIE) and Alaska (Ala-SIE) is found to account for about 65% and 21% of the Arctic SIE interannual variability, respectively. Variability in Ala-SIE is related to the GL-high, whereas variability in Sib-SIE is related to the CA-high. A decreased Ala-SIE is associated with decreased cloud cover and increased easterly winds along the Alaskan coast, promoting ice–albedo feedback. A decreased Sib-SIE is associated with a significant increase in water vapor and downward longwave radiation (DLR) along the Siberian coast. The years 2012 and 2020 with minimum recorded ASIE are used as examples. Compared to climatology, summer 2012 is characterized by a significantly enhanced GL-high with major sea ice loss along the Alaskan coast, while summer 2020 is characterized by an enhanced CA-high with sea ice loss focused along the Siberian coast. In 2012, the lack of cloud cover along the Alaskan coast contributed to an increase in incoming solar radiation, amplifying ice–albedo feedback there; while in 2020, the opposite occurs with an increase in cloud cover along the Alaskan coast, resulting in a slight increase in sea ice there. Along the Siberian coast, increased DLR in 2020 plays a dominant role in sea ice loss, and increased cloud cover and water vapor both contribute to the increased DLR.
, Available online
, Manuscript accepted 14 September 2022, doi: 10.1007/s00376-022-1460-4
Abstract:
This study assesses sea ice thickness (SIT) from the historical run of the Coupled Model Inter-comparison Project Phase 6 (CMIP6). The SIT reanalysis from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) product is chosen as the validation reference data. Results show that most models can adequately reproduce the climatological mean, seasonal cycle, and long-term trend of Arctic Ocean SIT during 1979–2014, but significant inter-model spread exists. Differences in simulated SIT patterns among the CMIP6 models may be related to model resolution and sea ice model components. By comparing the climatological mean and trend for SIT among all models, the Arctic SIT change in different seas during 1979–2014 is evaluated. Under the scenario of historical radiative forcing, the Arctic SIT will probably exponentially decay at –18% (10 yr)–1 and plausibly reach its minimum (equilibrium) of 0.47 m since the 2070s.
This study assesses sea ice thickness (SIT) from the historical run of the Coupled Model Inter-comparison Project Phase 6 (CMIP6). The SIT reanalysis from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) product is chosen as the validation reference data. Results show that most models can adequately reproduce the climatological mean, seasonal cycle, and long-term trend of Arctic Ocean SIT during 1979–2014, but significant inter-model spread exists. Differences in simulated SIT patterns among the CMIP6 models may be related to model resolution and sea ice model components. By comparing the climatological mean and trend for SIT among all models, the Arctic SIT change in different seas during 1979–2014 is evaluated. Under the scenario of historical radiative forcing, the Arctic SIT will probably exponentially decay at –18% (10 yr)–1 and plausibly reach its minimum (equilibrium) of 0.47 m since the 2070s.
, Available online
, Manuscript accepted 16 August 2022, doi: 10.1007/s00376-022-2033-2
Abstract:
This study examines the dependence of Arctic stratospheric polar vortex (SPV) variations on the meridional positions of the sea surface temperature (SST) anomalies associated with the first leading mode of North Pacific SST. The principal component 1 (PC1) of the first leading mode is obtained by empirical orthogonal function decomposition. Reanalysis data, numerical experiments, and CMIP5 model outputs all suggest that the PC1 events (positive-minus-negative PC1 events), located relatively northward (i.e., North PC1 events), more easily weaken the Arctic SPV compared to the PC1 events located relatively southward (i.e., South PC1 events). The analysis indicates that the North PC1-related Aleutian low anomaly is located over the northern North Pacific and thus enhances the climatological trough, which strengthens the planetary-scale wave 1 at mid-to-high latitudes and thereby weakens the SPV. The weakened stratospheric circulation further extends into the troposphere and favors negative surface temperature anomalies over Eurasia. By contrast, the South PC1-related Aleutian low anomaly is located relatively southward, and its constructive interference with the climatological trough is less efficient at high latitudes. Thus, the South PC1 events could not induce an evident enhancement of the planetary-scale waves at high latitudes and thereby a weakening of the SPV on average. The Eurasian cooling associated with South PC1 events (positive-minus-negative PC1 events) is also not prominent. The results of this study suggest that the meridional positions of the PC1 events may be useful for predicting the Arctic SPV and Eurasian surface temperature variations.
This study examines the dependence of Arctic stratospheric polar vortex (SPV) variations on the meridional positions of the sea surface temperature (SST) anomalies associated with the first leading mode of North Pacific SST. The principal component 1 (PC1) of the first leading mode is obtained by empirical orthogonal function decomposition. Reanalysis data, numerical experiments, and CMIP5 model outputs all suggest that the PC1 events (positive-minus-negative PC1 events), located relatively northward (i.e., North PC1 events), more easily weaken the Arctic SPV compared to the PC1 events located relatively southward (i.e., South PC1 events). The analysis indicates that the North PC1-related Aleutian low anomaly is located over the northern North Pacific and thus enhances the climatological trough, which strengthens the planetary-scale wave 1 at mid-to-high latitudes and thereby weakens the SPV. The weakened stratospheric circulation further extends into the troposphere and favors negative surface temperature anomalies over Eurasia. By contrast, the South PC1-related Aleutian low anomaly is located relatively southward, and its constructive interference with the climatological trough is less efficient at high latitudes. Thus, the South PC1 events could not induce an evident enhancement of the planetary-scale waves at high latitudes and thereby a weakening of the SPV on average. The Eurasian cooling associated with South PC1 events (positive-minus-negative PC1 events) is also not prominent. The results of this study suggest that the meridional positions of the PC1 events may be useful for predicting the Arctic SPV and Eurasian surface temperature variations.
, Available online
, Manuscript accepted 04 August 2022, doi: 10.1007/s00376-022-2079-1
Abstract:
The prediction of summer precipitation over the Yangtze River basin (YRB) has long been challenging, especially during June–July (JJ), when the mei-yu generally occurs. This study explores the potential signal for the YRB precipitation in JJ and reveals that the Tibetan Plateau tropospheric temperature (TPTT) in the middle and upper levels during the preceding December–January (DJ) is significantly correlated with JJ YRB precipitation. The close connection between the DJ TPTT anomaly with JJ YRB precipitation may be due to the joint modulation of the DJ ENSO and spring TP soil temperatures. The lagged response to an anomalously cold TPTT during the preceding DJ is a TPTT that is still anomalously cold during the following JJ. The lower TPTT can lead to an anomalous anticyclone to the east of Lake Baikal, an anomalous cyclone at the middle latitudes of East Asia, and an anomalous anticyclone over the western North Pacific. Meanwhile, the East Asian westerly jet shifts southward in response to the meridional thermal gradient caused by the colder troposphere extending from the TP to the east of Lake Baikal. The above-mentioned circulation anomalies constitute the positive anomaly of the East Asia-Pacific pattern, known to be conducive to more precipitation over the YRB. Since the DJ TPTT contains both the land (TP soil temperature) and ocean (ENSO) signals, it has a closer relationship with the JJ precipitation over the YRB than the DJ ENSO alone. Therefore, the preceding DJ TPTT can be considered an alternative predictor of the JJ YRB precipitation.
The prediction of summer precipitation over the Yangtze River basin (YRB) has long been challenging, especially during June–July (JJ), when the mei-yu generally occurs. This study explores the potential signal for the YRB precipitation in JJ and reveals that the Tibetan Plateau tropospheric temperature (TPTT) in the middle and upper levels during the preceding December–January (DJ) is significantly correlated with JJ YRB precipitation. The close connection between the DJ TPTT anomaly with JJ YRB precipitation may be due to the joint modulation of the DJ ENSO and spring TP soil temperatures. The lagged response to an anomalously cold TPTT during the preceding DJ is a TPTT that is still anomalously cold during the following JJ. The lower TPTT can lead to an anomalous anticyclone to the east of Lake Baikal, an anomalous cyclone at the middle latitudes of East Asia, and an anomalous anticyclone over the western North Pacific. Meanwhile, the East Asian westerly jet shifts southward in response to the meridional thermal gradient caused by the colder troposphere extending from the TP to the east of Lake Baikal. The above-mentioned circulation anomalies constitute the positive anomaly of the East Asia-Pacific pattern, known to be conducive to more precipitation over the YRB. Since the DJ TPTT contains both the land (TP soil temperature) and ocean (ENSO) signals, it has a closer relationship with the JJ precipitation over the YRB than the DJ ENSO alone. Therefore, the preceding DJ TPTT can be considered an alternative predictor of the JJ YRB precipitation.
, Available online
, Manuscript accepted 04 August 2022, doi: 10.1007/s00376-022-2040-3
Abstract:
Sea ice, one of the most dominant barriers to Arctic shipping, has decreased dramatically over the past four decades. Arctic maritime transport is hereupon growing in recent years. To produce a long-term assessment of trans-Arctic accessibility, we systematically revisit the daily Arctic navigability with a view to the combined effects of sea ice thickness and concentration throughout the period 1979−2020. The general trends of Navigable Windows (NW) in the Northeast Passage show that the number of navigable days is steadily growing and reached 89±16 days for Open Water (OW) ships and 163±19 days for Polar Class 6 (PC6) ships in the 2010s, despite high interannual and interdecadal variability in the NWs. More consecutive NWs have emerged annually for both OW ships and PC6 ships since 2005 because of the faster sea ice retreat. Since the 1980s, the number of simulated Arctic routes has continuously increased, and optimal navigability exists in these years of record-low sea ice extent (e.g., 2012 and 2020). Summertime navigability in the East Siberian and Laptev Seas, on the other hand, varies dramatically due to changing sea ice conditions. This systematic assessment of Arctic navigability provides a reference for better projecting the future trans-Arctic shipping routes.
Sea ice, one of the most dominant barriers to Arctic shipping, has decreased dramatically over the past four decades. Arctic maritime transport is hereupon growing in recent years. To produce a long-term assessment of trans-Arctic accessibility, we systematically revisit the daily Arctic navigability with a view to the combined effects of sea ice thickness and concentration throughout the period 1979−2020. The general trends of Navigable Windows (NW) in the Northeast Passage show that the number of navigable days is steadily growing and reached 89±16 days for Open Water (OW) ships and 163±19 days for Polar Class 6 (PC6) ships in the 2010s, despite high interannual and interdecadal variability in the NWs. More consecutive NWs have emerged annually for both OW ships and PC6 ships since 2005 because of the faster sea ice retreat. Since the 1980s, the number of simulated Arctic routes has continuously increased, and optimal navigability exists in these years of record-low sea ice extent (e.g., 2012 and 2020). Summertime navigability in the East Siberian and Laptev Seas, on the other hand, varies dramatically due to changing sea ice conditions. This systematic assessment of Arctic navigability provides a reference for better projecting the future trans-Arctic shipping routes.
, Available online
, Manuscript accepted 18 July 2022, doi: 10.1007/s00376-022-2057-7
Abstract:
How atmospheric and oceanic circulations respond to Arctic warming at different timescales are revealed with idealized numerical simulations. Induced by local forcing and feedback, Arctic warming appears and leads to sea-ice melting. Deep-water formation is inhibited, which weakens the Atlantic Meridional Overturning Circulation (AMOC). The flow and temperature in the upper layer does not respond to the AMOC decrease immediately, especially at mid-low latitudes. Thus, nearly uniform surface warming in mid-low latitudes enhances (decreases) the strength (width) of the Hadley cell (HC). With the smaller northward heat carried by the weaker AMOC, the Norwegian Sea cools significantly. With strong warming in Northern Hemisphere high latitudes, the long-term response triggers the “temperature-wind-gyre-temperature” cycle, leading to colder midlatitudes, resulting in strong subsidence and Ferrel cell enhancement, which drives the HC southward. With weaker warming in the tropics and stronger warming at high latitudes, there is a stronger HC with decreased width. A much warmer Southern Hemisphere appears due to a weaker AMOC that also pushes the HC southward. Our idealized model results suggest that the HC strengthens under both warming conditions, as tropical warming determines the strength of the HC convection. Second, extreme Arctic warming led by artificially reduced surface albedo decreases the meridional temperature gradient between high and low latitudes, which contracts the HC. Third, a warmer mid-high latitude in the Northern (Southern) Hemisphere due to surface albedo feedback (weakened AMOC) in our experiments pushes the HC northward (southward). In most seasons, the HC exhibits the same trend as that described above.
How atmospheric and oceanic circulations respond to Arctic warming at different timescales are revealed with idealized numerical simulations. Induced by local forcing and feedback, Arctic warming appears and leads to sea-ice melting. Deep-water formation is inhibited, which weakens the Atlantic Meridional Overturning Circulation (AMOC). The flow and temperature in the upper layer does not respond to the AMOC decrease immediately, especially at mid-low latitudes. Thus, nearly uniform surface warming in mid-low latitudes enhances (decreases) the strength (width) of the Hadley cell (HC). With the smaller northward heat carried by the weaker AMOC, the Norwegian Sea cools significantly. With strong warming in Northern Hemisphere high latitudes, the long-term response triggers the “temperature-wind-gyre-temperature” cycle, leading to colder midlatitudes, resulting in strong subsidence and Ferrel cell enhancement, which drives the HC southward. With weaker warming in the tropics and stronger warming at high latitudes, there is a stronger HC with decreased width. A much warmer Southern Hemisphere appears due to a weaker AMOC that also pushes the HC southward. Our idealized model results suggest that the HC strengthens under both warming conditions, as tropical warming determines the strength of the HC convection. Second, extreme Arctic warming led by artificially reduced surface albedo decreases the meridional temperature gradient between high and low latitudes, which contracts the HC. Third, a warmer mid-high latitude in the Northern (Southern) Hemisphere due to surface albedo feedback (weakened AMOC) in our experiments pushes the HC northward (southward). In most seasons, the HC exhibits the same trend as that described above.
, Available online
, Manuscript accepted 11 February 2022, doi: 10.1007/s00376-022-0421-y
Abstract:
Using linear regression and composite analyses, this study identifies a pronounced asymmetric connection of sea surface temperature (SST) in the Tasman Sea with the two opposite phases of El Niño-Southern Oscillation (ENSO) during austral summer. In El Niño years, the SST anomalies (SSTAs) in the Tasman Sea exhibit a dipolar pattern with weak warmth in the northwest and modest cooling in the southeast, while during La Niña years the SSTAs exhibit a basin-scale warmth with greater amplitude. Investigations on the underlying mechanism suggest that this asymmetry arises from the oceanic heat transport, especially the anomalous Ekman meridional heat fluxes induced by the zonal wind stress anomalies, rather than the surface heat fluxes on the air-sea interface. A further analysis demonstrates that the asymmetry of oceanic heat transport between El Niño and La Niña years is driven by the asymmetric atmospheric circulation over the Tasman Sea stimulated by the asymmetric diabatic heating in the tropical Pacific between the two opposite ENSO phases.
Using linear regression and composite analyses, this study identifies a pronounced asymmetric connection of sea surface temperature (SST) in the Tasman Sea with the two opposite phases of El Niño-Southern Oscillation (ENSO) during austral summer. In El Niño years, the SST anomalies (SSTAs) in the Tasman Sea exhibit a dipolar pattern with weak warmth in the northwest and modest cooling in the southeast, while during La Niña years the SSTAs exhibit a basin-scale warmth with greater amplitude. Investigations on the underlying mechanism suggest that this asymmetry arises from the oceanic heat transport, especially the anomalous Ekman meridional heat fluxes induced by the zonal wind stress anomalies, rather than the surface heat fluxes on the air-sea interface. A further analysis demonstrates that the asymmetry of oceanic heat transport between El Niño and La Niña years is driven by the asymmetric atmospheric circulation over the Tasman Sea stimulated by the asymmetric diabatic heating in the tropical Pacific between the two opposite ENSO phases.
Abstract:
Previous numerical studies have focused on the combined effect of momentum and scalar eddy diffusivity on the intensity and structure of tropical cyclones. The separate impact of each eddy diffusivity estimated by planetary boundary layer (PBL) parameterization on the tropical cyclones has not yet been systematically examined. We therefore examined the separate impacts of moisture eddy diffusion on idealized tropical cyclones using Advanced Research Weather Research and Forecasting model with the Yonsei University PBL scheme. Our results show nonlinear effects of moisture eddy diffusivity on the simulation of idealized tropical cyclones. Increasing the moisture eddy diffusion increases the moisture content of the PBL, with three different effects on tropical cyclones: (1) an increase in the depth of the PBL; (2) an increase in convection in the inner rain band and eyewall; (3) drying of the lowest region of the PBL and then increasing the surface latent heat flux. These three processes have different effects on the intensity and structure of the tropical cyclone through various physical mechanisms. The increased surface latent heat flux is mainly responsible for the decrease in pressure. Results show that moisture eddy diffusivity has clear effects on the pressure in tropical cyclones, but contributes little to the wind intensity. This largely influences the wind–pressure relationship, which is crucial in tropical cyclones simulation. These results improve our understanding of moisture eddy diffusivity in the PBL and its influence on tropical cyclones and provides guidance for interpreting the variation of the PBL moisture in tropical cyclone simulations.
Previous numerical studies have focused on the combined effect of momentum and scalar eddy diffusivity on the intensity and structure of tropical cyclones. The separate impact of each eddy diffusivity estimated by planetary boundary layer (PBL) parameterization on the tropical cyclones has not yet been systematically examined. We therefore examined the separate impacts of moisture eddy diffusion on idealized tropical cyclones using Advanced Research Weather Research and Forecasting model with the Yonsei University PBL scheme. Our results show nonlinear effects of moisture eddy diffusivity on the simulation of idealized tropical cyclones. Increasing the moisture eddy diffusion increases the moisture content of the PBL, with three different effects on tropical cyclones: (1) an increase in the depth of the PBL; (2) an increase in convection in the inner rain band and eyewall; (3) drying of the lowest region of the PBL and then increasing the surface latent heat flux. These three processes have different effects on the intensity and structure of the tropical cyclone through various physical mechanisms. The increased surface latent heat flux is mainly responsible for the decrease in pressure. Results show that moisture eddy diffusivity has clear effects on the pressure in tropical cyclones, but contributes little to the wind intensity. This largely influences the wind–pressure relationship, which is crucial in tropical cyclones simulation. These results improve our understanding of moisture eddy diffusivity in the PBL and its influence on tropical cyclones and provides guidance for interpreting the variation of the PBL moisture in tropical cyclone simulations.
, Available online
, Manuscript accepted 10 November 2020, doi: 10.1007/s00376-020-0169-5
Abstract:
Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land–atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves—one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m−2 and 51.55/17.92 W m−2, respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m−2, 82.56 W m−2 and 72.46 W m−2, respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.
Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land–atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves—one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m−2 and 51.55/17.92 W m−2, respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m−2, 82.56 W m−2 and 72.46 W m−2, respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.
CAS-ESM2.0 Successfully Reproduces Historical Atmospheric CO2 in a Coupled Carbon−Climate Simulation
, Available online
, Manuscript accepted 14 September 2023, doi: 10.1007/s00376-023-3172-9
Abstract:
The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon–climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon–climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon–climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China’s goal of carbon neutrality.
The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon–climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon–climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon–climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China’s goal of carbon neutrality.
, Available online
, Manuscript accepted 04 September 2023, doi: 10.1007/s00376-023-3171-x
Abstract:
Extreme weather events and their consequential impacts have been a key feature of the climate in recent years in many parts of the world, with many partly attributed to ongoing global-scale warming. The past year, 2022, has been no exception, with further records being broken. The year was marked by unprecedented heatwaves and droughts with highly unusual spatial extent, duration and intensity, with one measure indicating an aggregated and overall intensity of extreme heat events worldwide not seen since at least 1950. The extreme drought measured by surface soil moisture covered 47.3% of global land areas in 2022, which was the second most widespread year since 1980. Here, we examine notable events of the year in five major regions of the world: China’s Yangtze River region, western Europe, the western U.S., the Horn of Africa and central South America. For each event, we review the potential roles of circulation, oceanic forcing (especially the “triple-dip” La Niña) and anthropogenic climate change, with an aim of understanding the extreme events in 2022 from a global perspective. This will serve as a reference for mechanism understanding, prediction and attribution of extreme events.
Extreme weather events and their consequential impacts have been a key feature of the climate in recent years in many parts of the world, with many partly attributed to ongoing global-scale warming. The past year, 2022, has been no exception, with further records being broken. The year was marked by unprecedented heatwaves and droughts with highly unusual spatial extent, duration and intensity, with one measure indicating an aggregated and overall intensity of extreme heat events worldwide not seen since at least 1950. The extreme drought measured by surface soil moisture covered 47.3% of global land areas in 2022, which was the second most widespread year since 1980. Here, we examine notable events of the year in five major regions of the world: China’s Yangtze River region, western Europe, the western U.S., the Horn of Africa and central South America. For each event, we review the potential roles of circulation, oceanic forcing (especially the “triple-dip” La Niña) and anthropogenic climate change, with an aim of understanding the extreme events in 2022 from a global perspective. This will serve as a reference for mechanism understanding, prediction and attribution of extreme events.
, Available online
, Manuscript accepted 15 August 2023, doi: 10.1007/s00376-023-3107-5
Abstract:
In this study, we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network (LUCCN) prototype. The LUCCN primarily consists of two categories of instruments, including ground-based and UAV-based in-situ measurement. We use the GMP343, a low-cost non-dispersive infrared sensor, in both ground-based and UAV-based instruments. The first integrated measurement campaign took place in Shenzhen, China, 4 May 2023. During the campaign, we found that LUCCN’s UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources, which was especially obvious at a gas power plant in Shenzhen. The emission flux was calculated by a cross-sectional flux (CSF) method, the results of which differed from the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC). The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross section. The LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information, especially in scenarios involving the detection of smaller-scale, rapidly varying sources and sinks.
In this study, we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network (LUCCN) prototype. The LUCCN primarily consists of two categories of instruments, including ground-based and UAV-based in-situ measurement. We use the GMP343, a low-cost non-dispersive infrared sensor, in both ground-based and UAV-based instruments. The first integrated measurement campaign took place in Shenzhen, China, 4 May 2023. During the campaign, we found that LUCCN’s UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources, which was especially obvious at a gas power plant in Shenzhen. The emission flux was calculated by a cross-sectional flux (CSF) method, the results of which differed from the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC). The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross section. The LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information, especially in scenarios involving the detection of smaller-scale, rapidly varying sources and sinks.
, Available online
, Manuscript accepted 24 April 2023, doi: 10.1007/s00376-023-2347-8
Abstract:
HadISDH.extremes is an annually updated global gridded monthly monitoring product of wet and dry bulb temperature–based extremes indices, from January 1973 to December 2022. Data quality, including spatial and temporal stability, is a key focus. The hourly data are quality controlled. Homogeneity is assessed on monthly means and used to score each gridbox according to its homogeneity rather than to apply adjustments. This enables user-specific screening for temporal stability and avoids errors from inferring adjustments from monthly means for the daily maximum values. For general use, a score (HQ Flag) of 0 to 6 is recommended. A range of indices are presented, aligning with existing standardised indices. Uniquely, provision of both wet and dry bulb indices allows exploration of heat event character — whether it is a “humid and hot”, “dry and hot” or “humid and warm” event. It is designed for analysis of long-term trends in regional features. HadISDH.extremes can be used to study local events, but given the greater vulnerability to errors of maximum compared to mean values, cross-validation with independent information is advised.
HadISDH.extremes is an annually updated global gridded monthly monitoring product of wet and dry bulb temperature–based extremes indices, from January 1973 to December 2022. Data quality, including spatial and temporal stability, is a key focus. The hourly data are quality controlled. Homogeneity is assessed on monthly means and used to score each gridbox according to its homogeneity rather than to apply adjustments. This enables user-specific screening for temporal stability and avoids errors from inferring adjustments from monthly means for the daily maximum values. For general use, a score (HQ Flag) of 0 to 6 is recommended. A range of indices are presented, aligning with existing standardised indices. Uniquely, provision of both wet and dry bulb indices allows exploration of heat event character — whether it is a “humid and hot”, “dry and hot” or “humid and warm” event. It is designed for analysis of long-term trends in regional features. HadISDH.extremes can be used to study local events, but given the greater vulnerability to errors of maximum compared to mean values, cross-validation with independent information is advised.
, Available online
, Manuscript accepted 08 November 2022, doi: 10.1007/s00376-022-2197-9
Abstract:
Northeast Asian cut-off lows are crucial cyclonic systems that can bring temperature and precipitation extremes over large areas. Skillful subseasonal forecasting of Northeast Asian cut-off lows is of great importance. Using two dynamical forecasting systems, one from the Beijing Climate Center (BCC-CSM2-HR) and the other from the Met Office (GloSea5), this study assesses simulation ability and subseasonal prediction skill for early-summer Northeast Asian cut-off lows. Both models are shown to have good ability in representing the spatial structure of cut-off lows, but they underestimate the intensity. The skillful prediction time scales for cut-off low intensity are about 10.2 days for BCC-CSM2-HR and 11.4 days for GloSea5 in advance. Further examination shows that both models can essentially capture the initial Rossby wave train,rapid growth and decay processes responsible for the evolution of cut-off lows, but the models show weaker amplitudes for the three-stage processes. The underestimated simulated strength of both the Eurasian midlatitude and East Asian subtropical jets may lead to the weaker local eddy-mean flow interaction responsible for the cut-off low evolution.
Northeast Asian cut-off lows are crucial cyclonic systems that can bring temperature and precipitation extremes over large areas. Skillful subseasonal forecasting of Northeast Asian cut-off lows is of great importance. Using two dynamical forecasting systems, one from the Beijing Climate Center (BCC-CSM2-HR) and the other from the Met Office (GloSea5), this study assesses simulation ability and subseasonal prediction skill for early-summer Northeast Asian cut-off lows. Both models are shown to have good ability in representing the spatial structure of cut-off lows, but they underestimate the intensity. The skillful prediction time scales for cut-off low intensity are about 10.2 days for BCC-CSM2-HR and 11.4 days for GloSea5 in advance. Further examination shows that both models can essentially capture the initial Rossby wave train,rapid growth and decay processes responsible for the evolution of cut-off lows, but the models show weaker amplitudes for the three-stage processes. The underestimated simulated strength of both the Eurasian midlatitude and East Asian subtropical jets may lead to the weaker local eddy-mean flow interaction responsible for the cut-off low evolution.
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