2020 Vol. 37, No. 4
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2020, 37(4): 307-317.
doi: 10.1007/s00376-019-9222-7
Abstract:
The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate. Many investigations have been conducted to reveal the relationship between the Arctic and Eurasian extreme events from the perspective of climatological statistics. As a prediction source for extreme events in Eurasia, Arctic conditions are crucial for extreme event predictions. Therefore, it is urgent to explore the Arctic influence on the predictability of Eurasian extreme events due to the large uncertainties in Arctic conditions. Considering the sensitivity and nonlinearity of the atmospheric circulations in midlatitude to Arctic conditions, it is necessary to investigate the Arctic influences on Eurasian extreme weather events in case studies at weather time scales. Previous studies indicate that only perturbations in specific patterns have fast growth. Thus, the conditional nonlinear optimal perturbation approach is recommended for exploring the uncertainties in Arctic initial and boundary conditions and their synergistic effect on Eurasian extreme events. Moreover, the mechanism for extreme event formation may differ in different cases. Therefore, more extreme cases should be investigated to reach robust conclusions.
The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate. Many investigations have been conducted to reveal the relationship between the Arctic and Eurasian extreme events from the perspective of climatological statistics. As a prediction source for extreme events in Eurasia, Arctic conditions are crucial for extreme event predictions. Therefore, it is urgent to explore the Arctic influence on the predictability of Eurasian extreme events due to the large uncertainties in Arctic conditions. Considering the sensitivity and nonlinearity of the atmospheric circulations in midlatitude to Arctic conditions, it is necessary to investigate the Arctic influences on Eurasian extreme weather events in case studies at weather time scales. Previous studies indicate that only perturbations in specific patterns have fast growth. Thus, the conditional nonlinear optimal perturbation approach is recommended for exploring the uncertainties in Arctic initial and boundary conditions and their synergistic effect on Eurasian extreme events. Moreover, the mechanism for extreme event formation may differ in different cases. Therefore, more extreme cases should be investigated to reach robust conclusions.
2020, 37(4): 318-327.
doi: 10.1007/s00376-020-9180-0
Abstract:
Surface relative humidity (RH) is a key element for weather and climate monitoring and research. However, RH is not as commonly applied in studying climate change, partly because the observation series of RH are prone to inhomogeneous biases due to non-climate changes in the observation system. A homogenized dataset of daily RH series from 746 stations in Chinese mainland for the period 1960–2017, ChinaRHv1.0, has been developed. Most (685 or 91.82% of the total) station time series were inhomogeneous with one or more break points. The major breakpoints occurred in the early 2000s for many stations, especially in the humid and semi-humid zones, due to the implementation of automated observation across the country. The inhomogeneous biases in the early manual records before this change are positive relative to the recent automatic records, for most of the biased station series. There are more break points detected by using the MASH (Multiple Analysis of Series for Homogenization) method, with biases mainly around −0.5% and 0.5%. These inhomogeneous biases are adjusted with reference to the most recent observations for each station. Based on the adjusted observations, the regional mean RH series of China shows little long-term trend during 1960–2017 [0.006% (10 yr)−1], contrasting with a false decreasing trend [−0.414% (10 yr)−1] in the raw data. It is notable that ERA5 reanalysis data match closely with the interannual variations of the raw RH series in China, including the jump in the early 2000s, raising a caveat for its application in studying climate change in the region.
Surface relative humidity (RH) is a key element for weather and climate monitoring and research. However, RH is not as commonly applied in studying climate change, partly because the observation series of RH are prone to inhomogeneous biases due to non-climate changes in the observation system. A homogenized dataset of daily RH series from 746 stations in Chinese mainland for the period 1960–2017, ChinaRHv1.0, has been developed. Most (685 or 91.82% of the total) station time series were inhomogeneous with one or more break points. The major breakpoints occurred in the early 2000s for many stations, especially in the humid and semi-humid zones, due to the implementation of automated observation across the country. The inhomogeneous biases in the early manual records before this change are positive relative to the recent automatic records, for most of the biased station series. There are more break points detected by using the MASH (Multiple Analysis of Series for Homogenization) method, with biases mainly around −0.5% and 0.5%. These inhomogeneous biases are adjusted with reference to the most recent observations for each station. Based on the adjusted observations, the regional mean RH series of China shows little long-term trend during 1960–2017 [0.006% (10 yr)−1], contrasting with a false decreasing trend [−0.414% (10 yr)−1] in the raw data. It is notable that ERA5 reanalysis data match closely with the interannual variations of the raw RH series in China, including the jump in the early 2000s, raising a caveat for its application in studying climate change in the region.
2020, 37(4): 328-346.
doi: 10.1007/s00376-020-9171-1
Abstract:
To represent model uncertainties more comprehensively, a stochastically perturbed parameterization (SPP) scheme consisting of temporally and spatially varying perturbations of 18 parameters in the microphysics, convection, boundary layer, and surface layer parameterization schemes, as well as the stochastically perturbed parameterization tendencies (SPPT) scheme, and the stochastic kinetic energy backscatter (SKEB) scheme, is applied in the Global and Regional Assimilation and Prediction Enhanced System—Regional Ensemble Prediction System (GRAPES-REPS) to evaluate and compare the general performance of various combinations of multiple stochastic physics schemes. Six experiments are performed for a summer month (1–30 June 2015) over China and multiple verification metrics are used. The results show that: (1) All stochastic experiments outperform the control (CTL) experiment, and all combinations of stochastic parameterization schemes perform better than the single SPP scheme, indicating that stochastic methods can effectively improve the forecast skill, and combinations of multiple stochastic parameterization schemes can better represent model uncertainties; (2) The combination of all three stochastic physics schemes (SPP, SPPT, and SKEB) outperforms any other combination of two schemes in precipitation forecasting and surface and upper-air verification to better represent the model uncertainties and improve the forecast skill; (3) Combining SKEB with SPP and/or SPPT results in a notable increase in the spread and reduction in outliers for the upper-air wind speed. SKEB directly perturbs the wind field and therefore its addition will greatly impact the upper-air wind-speed fields, and it contributes most to the improvement in spread and outliers for wind; (4) The introduction of SPP has a positive added value, and does not lead to large changes in the evolution of the kinetic energy (KE) spectrum at any wavelength; (5) The introduction of SPPT and SKEB would cause a 5%–10% and 30%–80% change in the KE of mesoscale systems, and all three stochastic schemes (SPP, SPPT, and SKEB) mainly affect the KE of mesoscale systems. This study indicates the potential of combining multiple stochastic physics schemes and lays a foundation for the future development and design of regional and global ensembles.
To represent model uncertainties more comprehensively, a stochastically perturbed parameterization (SPP) scheme consisting of temporally and spatially varying perturbations of 18 parameters in the microphysics, convection, boundary layer, and surface layer parameterization schemes, as well as the stochastically perturbed parameterization tendencies (SPPT) scheme, and the stochastic kinetic energy backscatter (SKEB) scheme, is applied in the Global and Regional Assimilation and Prediction Enhanced System—Regional Ensemble Prediction System (GRAPES-REPS) to evaluate and compare the general performance of various combinations of multiple stochastic physics schemes. Six experiments are performed for a summer month (1–30 June 2015) over China and multiple verification metrics are used. The results show that: (1) All stochastic experiments outperform the control (CTL) experiment, and all combinations of stochastic parameterization schemes perform better than the single SPP scheme, indicating that stochastic methods can effectively improve the forecast skill, and combinations of multiple stochastic parameterization schemes can better represent model uncertainties; (2) The combination of all three stochastic physics schemes (SPP, SPPT, and SKEB) outperforms any other combination of two schemes in precipitation forecasting and surface and upper-air verification to better represent the model uncertainties and improve the forecast skill; (3) Combining SKEB with SPP and/or SPPT results in a notable increase in the spread and reduction in outliers for the upper-air wind speed. SKEB directly perturbs the wind field and therefore its addition will greatly impact the upper-air wind-speed fields, and it contributes most to the improvement in spread and outliers for wind; (4) The introduction of SPP has a positive added value, and does not lead to large changes in the evolution of the kinetic energy (KE) spectrum at any wavelength; (5) The introduction of SPPT and SKEB would cause a 5%–10% and 30%–80% change in the KE of mesoscale systems, and all three stochastic schemes (SPP, SPPT, and SKEB) mainly affect the KE of mesoscale systems. This study indicates the potential of combining multiple stochastic physics schemes and lays a foundation for the future development and design of regional and global ensembles.
2020, 37(4): 347-358.
doi: 10.1007/s00376-020-9165-z
Abstract:
In China and East Asia, the long-term continuous observational data at daily resolution are insufficient, and thus there is a lack of good understanding of the extreme climate variation over the last 100 years plus. In this study, the extreme temperature indices defined by ETCCDI (Expert Team on Climate Change Detection and Indices) and local meteorological administrations were analyzed for Changchun City, Northeast China, by using the daily maximum temperature (Tmax) and daily minimum temperature (Tmin) over 1909−2018. The results showed that extreme cold events, such as cold days, cold nights, frost days, icing days, and low temperature days, decreased significantly at rates of −0.41 d (10 yr)−1, −1.45 d (10 yr)−1, −2.28 d (10 yr)−1, −1.16 d (10 yr)−1 and −1.90 d (10 yr)−1, respectively. Warm nights increased significantly at a rate of 1.71 d (10 yr)−1, but warm days decreased slightly and the number of high temperature days decreased at a rate of −0.20 d (10 yr)−1. The frequency of cold surge events increased significantly at a rate of 0.25 d (10 yr)−1, occurring mainly from the mid-1950s to late-1980s. The average Tmax, average Tmin and extreme Tmin increased at rates of 0.09°C (10 yr)−1, 0.36°C (10 yr)−1 and 0.54°C (10 yr)−1, respectively; and extreme Tmax decreased significantly at a rate of −0.17°C (10 yr)−1. In 1909−2018, 1951−2018 and 1979−2018, the indices related to cold events decreased, while the trends of the indices related to warm events were different for different periods.
In China and East Asia, the long-term continuous observational data at daily resolution are insufficient, and thus there is a lack of good understanding of the extreme climate variation over the last 100 years plus. In this study, the extreme temperature indices defined by ETCCDI (Expert Team on Climate Change Detection and Indices) and local meteorological administrations were analyzed for Changchun City, Northeast China, by using the daily maximum temperature (Tmax) and daily minimum temperature (Tmin) over 1909−2018. The results showed that extreme cold events, such as cold days, cold nights, frost days, icing days, and low temperature days, decreased significantly at rates of −0.41 d (10 yr)−1, −1.45 d (10 yr)−1, −2.28 d (10 yr)−1, −1.16 d (10 yr)−1 and −1.90 d (10 yr)−1, respectively. Warm nights increased significantly at a rate of 1.71 d (10 yr)−1, but warm days decreased slightly and the number of high temperature days decreased at a rate of −0.20 d (10 yr)−1. The frequency of cold surge events increased significantly at a rate of 0.25 d (10 yr)−1, occurring mainly from the mid-1950s to late-1980s. The average Tmax, average Tmin and extreme Tmin increased at rates of 0.09°C (10 yr)−1, 0.36°C (10 yr)−1 and 0.54°C (10 yr)−1, respectively; and extreme Tmax decreased significantly at a rate of −0.17°C (10 yr)−1. In 1909−2018, 1951−2018 and 1979−2018, the indices related to cold events decreased, while the trends of the indices related to warm events were different for different periods.
2020, 37(4): 359-376.
doi: 10.1007/s00376-020-9204-9
Abstract:
The relationship between precipitation intensity and cloud water in typhoon systems remains unclear. This study combined time- and space-synchronized precipitation and spectral data obtained by the Precipitation Radar (PR) as well as the Visible and Infrared Scanner (VIRS) onboard the TRMM satellite, to overcome the limitations of precipitation properties and cloud parameters not being synchronized in previous studies. A merged dataset of near-surface rain rate (RR) and corresponding cloud water path (CWP) was established and used to analyze the potential correlation between cloud microphysical properties and precipitation, to deepen our understanding of the evolution of cloud to rain. In addition, 25 collocated satellite overpasses of mature typhoon cases in the Northwest Pacific Ocean from 1998 to 2012 were obtained, and the relationships between the CWP and RR of 144 515 pixels were analyzed in detail. The results show that the CWP and RR of mature typhoon systems with different precipitation types, precipitation cloud phases, and vertical depths of precipitation can be fitted by a notable sigmoid function, which may be useful for estimating CWP and parameterizing precipitation in models. Furthermore, the relationship was applied and tested with an independent sample to show that RR is a significant indicator of CWP.
The relationship between precipitation intensity and cloud water in typhoon systems remains unclear. This study combined time- and space-synchronized precipitation and spectral data obtained by the Precipitation Radar (PR) as well as the Visible and Infrared Scanner (VIRS) onboard the TRMM satellite, to overcome the limitations of precipitation properties and cloud parameters not being synchronized in previous studies. A merged dataset of near-surface rain rate (RR) and corresponding cloud water path (CWP) was established and used to analyze the potential correlation between cloud microphysical properties and precipitation, to deepen our understanding of the evolution of cloud to rain. In addition, 25 collocated satellite overpasses of mature typhoon cases in the Northwest Pacific Ocean from 1998 to 2012 were obtained, and the relationships between the CWP and RR of 144 515 pixels were analyzed in detail. The results show that the CWP and RR of mature typhoon systems with different precipitation types, precipitation cloud phases, and vertical depths of precipitation can be fitted by a notable sigmoid function, which may be useful for estimating CWP and parameterizing precipitation in models. Furthermore, the relationship was applied and tested with an independent sample to show that RR is a significant indicator of CWP.
2020, 37(4): 377-386.
doi: 10.1007/s00376-020-9236-1
Abstract:
Understanding the responses of mean and extreme precipitation to climate change is of great importance. Previous studies have mainly focused on the responses to prescribed sea surface warming or warming due to increases of CO2. This study uses a cloud-resolving model under the idealization of radiative–convective equilibrium to examine the responses of mean and extreme precipitation to a variety of climate forcings, including changes in prescribed sea surface temperature, CO2, solar insolation, surface albedo, stratospheric volcanic aerosols, and several tropospheric aerosols. The different responses of mean precipitation are understood by examining the changes in the surface energy budget. It is found that the cancellation between shortwave scattering and longwave radiation leads to a small dependence of the mean precipitation response on forcings. The responses of extreme precipitation are decomposed into three components (thermodynamic, dynamic, and precipitation efficiency). The thermodynamic components for all climate forcings are similar. The dynamic components and the precipitation-efficiency components, which have large spreads among the cases, are negatively correlated, leading to a small dependence of the extreme precipitation response on the forcings.
Understanding the responses of mean and extreme precipitation to climate change is of great importance. Previous studies have mainly focused on the responses to prescribed sea surface warming or warming due to increases of CO2. This study uses a cloud-resolving model under the idealization of radiative–convective equilibrium to examine the responses of mean and extreme precipitation to a variety of climate forcings, including changes in prescribed sea surface temperature, CO2, solar insolation, surface albedo, stratospheric volcanic aerosols, and several tropospheric aerosols. The different responses of mean precipitation are understood by examining the changes in the surface energy budget. It is found that the cancellation between shortwave scattering and longwave radiation leads to a small dependence of the mean precipitation response on forcings. The responses of extreme precipitation are decomposed into three components (thermodynamic, dynamic, and precipitation efficiency). The thermodynamic components for all climate forcings are similar. The dynamic components and the precipitation-efficiency components, which have large spreads among the cases, are negatively correlated, leading to a small dependence of the extreme precipitation response on the forcings.
2020, 37(4): 387-398.
doi: 10.1007/s00376-020-9160-4
Abstract:
A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms. Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations, which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO2 dry air mole fraction (XCO2). Based on the radiance measurements in the 0.76 μm O2A band, 1.61 μm (weak), and 2.06 μm (strong) CO2 bands, the current combination of the A-Band Preprocessor (ABP) algorithm and Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) algorithm passes around 20%–25% of all soundings, which means that some contaminated scenes also pass the screening process. In this work, three independent pairs of threshold parameters used in the ABP and IDP algorithms are sufficiently tuned until the overall pass rate is close to the monthly clear-sky fraction from the MODIS cloud mask. The tightened thresholds are applied to observations over land surfaces in Europe and Japan in 2016. The results show improvement of agreement and positive predictive value compared to the collocated MODIS cloud mask, especially in summer and fall. In addition, analysis indicates that XCO2 retrievals with more stringent thresholds are in closer agreement with measurements from collocated Total Carbon Column Observing Network (TCCON) sites.
A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms. Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations, which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO2 dry air mole fraction (XCO2). Based on the radiance measurements in the 0.76 μm O2A band, 1.61 μm (weak), and 2.06 μm (strong) CO2 bands, the current combination of the A-Band Preprocessor (ABP) algorithm and Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) algorithm passes around 20%–25% of all soundings, which means that some contaminated scenes also pass the screening process. In this work, three independent pairs of threshold parameters used in the ABP and IDP algorithms are sufficiently tuned until the overall pass rate is close to the monthly clear-sky fraction from the MODIS cloud mask. The tightened thresholds are applied to observations over land surfaces in Europe and Japan in 2016. The results show improvement of agreement and positive predictive value compared to the collocated MODIS cloud mask, especially in summer and fall. In addition, analysis indicates that XCO2 retrievals with more stringent thresholds are in closer agreement with measurements from collocated Total Carbon Column Observing Network (TCCON) sites.
2020, 37(4): 399-419.
doi: 10.1007/s00376-020-9202-y
Abstract:
Idealized numerical simulations are conducted in this study to comparatively investigate the characteristics of the stratiform sector in the outer rainbands of tropical cyclones (TCs) in lower- and upper-layer vertical wind shear (VWS) with moderate magnitude. Consistent with the results in previous studies, the outer rainband stratiform sector of the TCs simulated in both experiments is generally located downshear left. Upper-layer VWS tends to produce stronger asymmetric outflow at upper levels in the downshear-left quadrant than lower-layer shear. This stronger asymmetric outflow transports more water vapor radially outward from the inner core to the outer core at upper levels in the downshear-left quadrant in the upper-layer shear experiment. More depositional growth of both graupel and cloud ice thus occurs downshear left in upper layers in the outer core, yielding more diabatic heating and stronger upward motions, particularly in the stratiform-dominated part of the stratiform sector in the upper-layer shear experiment. Resultingly, a better-organized stratiform sector in the outer rainbands is found in the upper-layer VWS experiment than in the lower-layer VWS experiment. The diabatic heating associated with the stratiform sector produces strong midlevel outflow on the radially inward side of, and weak midlevel inflow on the radially outward side of, the heating core, with lower-level inflow beneath the midlevel outflow and upper-level inflow above. The upper-layer VWS tends to produce a deeper asymmetric inflow layer in the outer rainband stratiform sector, with more significant lower-level inflow and tangential jets in the upper-layer VWS experiment.
Idealized numerical simulations are conducted in this study to comparatively investigate the characteristics of the stratiform sector in the outer rainbands of tropical cyclones (TCs) in lower- and upper-layer vertical wind shear (VWS) with moderate magnitude. Consistent with the results in previous studies, the outer rainband stratiform sector of the TCs simulated in both experiments is generally located downshear left. Upper-layer VWS tends to produce stronger asymmetric outflow at upper levels in the downshear-left quadrant than lower-layer shear. This stronger asymmetric outflow transports more water vapor radially outward from the inner core to the outer core at upper levels in the downshear-left quadrant in the upper-layer shear experiment. More depositional growth of both graupel and cloud ice thus occurs downshear left in upper layers in the outer core, yielding more diabatic heating and stronger upward motions, particularly in the stratiform-dominated part of the stratiform sector in the upper-layer shear experiment. Resultingly, a better-organized stratiform sector in the outer rainbands is found in the upper-layer VWS experiment than in the lower-layer VWS experiment. The diabatic heating associated with the stratiform sector produces strong midlevel outflow on the radially inward side of, and weak midlevel inflow on the radially outward side of, the heating core, with lower-level inflow beneath the midlevel outflow and upper-level inflow above. The upper-layer VWS tends to produce a deeper asymmetric inflow layer in the outer rainband stratiform sector, with more significant lower-level inflow and tangential jets in the upper-layer VWS experiment.
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