Current Articles
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2024,
41(5):
1-1.
Abstract:
2024,
41(5):
767-776.
doi: 10.1007/s00376-023-3206-3
Abstract:
Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas, there is a deficiency of relevant research, operational techniques, and experience. This made providing meteorological services for this event particularly challenging. The China Meteorological Administration (CMA) Earth System Modeling and Prediction Centre, achieved breakthroughs in research on short- and medium-term deterministic and ensemble numerical predictions. Several key technologies crucial for precise winter weather services during the Winter Olympics were developed. A comprehensive framework, known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics, was established. Some of these advancements represent the highest level of capabilities currently available in China. The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality. This included achievements such as the “100-meter level, minute level” downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days. Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed, and many of these techniques have since been integrated into the CMA’s operational national forecasting systems. These accomplishments were facilitated by a dedicated weather forecasting and research initiative, in conjunction with the preexisting real-time operational forecasting systems of the CMA. This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project (SMART2022), and continues to play an important role in their Regional Association (RA) II Research Development Project (Hangzhou RDP). Therefore, the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming high-impact weather forecasting activities. This article provides an overview and assessment of this program and the operational national forecasting systems.
Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas, there is a deficiency of relevant research, operational techniques, and experience. This made providing meteorological services for this event particularly challenging. The China Meteorological Administration (CMA) Earth System Modeling and Prediction Centre, achieved breakthroughs in research on short- and medium-term deterministic and ensemble numerical predictions. Several key technologies crucial for precise winter weather services during the Winter Olympics were developed. A comprehensive framework, known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics, was established. Some of these advancements represent the highest level of capabilities currently available in China. The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality. This included achievements such as the “100-meter level, minute level” downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days. Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed, and many of these techniques have since been integrated into the CMA’s operational national forecasting systems. These accomplishments were facilitated by a dedicated weather forecasting and research initiative, in conjunction with the preexisting real-time operational forecasting systems of the CMA. This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project (SMART2022), and continues to play an important role in their Regional Association (RA) II Research Development Project (Hangzhou RDP). Therefore, the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming high-impact weather forecasting activities. This article provides an overview and assessment of this program and the operational national forecasting systems.
2024,
41(5):
777-783.
doi: 10.1007/s00376-023-3384-2
Abstract:
Central Asia consists of the former Soviet Republics, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. The region’s climate is continental, mostly semi-arid to arid. Agriculture is a significant part of the region’s economy. By its nature of intensive water use, agriculture is extremely vulnerable to climate change. Population growth and irrigation development have significantly increased the demand for water in the region. Major climate change issues include melting glaciers and a shrinking snowpack, which are the foundation of the region’s water resources, and a changing precipitation regime. Most glaciers are located in Kyrgyzstan and Tajikistan, leading to transboundary water resource issues. Summer already has extremely high temperatures. Analyses indicate that Central Asia has been warming and precipitation might be increasing. The warming is expected to increase, but its spatial and temporal distribution depends upon specific global scenarios. Projections of future precipitation show significant uncertainties in type, amount, and distribution. Regional Hydroclimate Projects (RHPs) are an approach to studying these issues. Initial steps to develop an RHP began in 2021 with a widely distributed online survey about these climate issues. It was followed up with an online workshop and then, in 2023, an in-person workshop, held in Tashkent, Uzbekistan. Priorities for the Global Energy and Water Exchanges (GEWEX) project for the region include both observations and modeling, as well as development of better and additional precipitation observations, all of which are topics for the next workshop. A well-designed RHP should lead to reductions in critical climate uncertainties in policy-relevant timeframes that can influence decisions on necessary investments in climate adaptation.
Central Asia consists of the former Soviet Republics, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. The region’s climate is continental, mostly semi-arid to arid. Agriculture is a significant part of the region’s economy. By its nature of intensive water use, agriculture is extremely vulnerable to climate change. Population growth and irrigation development have significantly increased the demand for water in the region. Major climate change issues include melting glaciers and a shrinking snowpack, which are the foundation of the region’s water resources, and a changing precipitation regime. Most glaciers are located in Kyrgyzstan and Tajikistan, leading to transboundary water resource issues. Summer already has extremely high temperatures. Analyses indicate that Central Asia has been warming and precipitation might be increasing. The warming is expected to increase, but its spatial and temporal distribution depends upon specific global scenarios. Projections of future precipitation show significant uncertainties in type, amount, and distribution. Regional Hydroclimate Projects (RHPs) are an approach to studying these issues. Initial steps to develop an RHP began in 2021 with a widely distributed online survey about these climate issues. It was followed up with an online workshop and then, in 2023, an in-person workshop, held in Tashkent, Uzbekistan. Priorities for the Global Energy and Water Exchanges (GEWEX) project for the region include both observations and modeling, as well as development of better and additional precipitation observations, all of which are topics for the next workshop. A well-designed RHP should lead to reductions in critical climate uncertainties in policy-relevant timeframes that can influence decisions on necessary investments in climate adaptation.
2024,
41(5):
784-800.
doi: 10.1007/s00376-023-3069-7
Abstract:
There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization (MP) schemes because of their complicated geometries and physical properties. Idealized supercell simulations are produced using the WRF model coupled with “full” Hebrew University spectral bin MP (HU-SBM), and NSSL and Thompson bulk MP (BMP) schemes. HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations, accompanied by less rain evaporation. HU-SBM produces more cloud ice (plates), graupel, and hail than the BMPs, yet precipitates less at the surface. The limiting mass bins (and subsequently, particle size) of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs. Aggregation from plates in HU-SBM, together with snow–graupel collisions, leads to a greater snow contribution to rain than those of the BMPs. Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes. Still, they are smaller in magnitude than bulk rain, NSSL hail, and Thompson graupel net fluxes near the surface. Conversely, the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions (PSDs) into spectral bins. The results highlight precipitation sensitivity to storm dynamics, fall speed, hydrometeor evolution governed by process rates, and MP PSD design.
There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization (MP) schemes because of their complicated geometries and physical properties. Idealized supercell simulations are produced using the WRF model coupled with “full” Hebrew University spectral bin MP (HU-SBM), and NSSL and Thompson bulk MP (BMP) schemes. HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations, accompanied by less rain evaporation. HU-SBM produces more cloud ice (plates), graupel, and hail than the BMPs, yet precipitates less at the surface. The limiting mass bins (and subsequently, particle size) of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs. Aggregation from plates in HU-SBM, together with snow–graupel collisions, leads to a greater snow contribution to rain than those of the BMPs. Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes. Still, they are smaller in magnitude than bulk rain, NSSL hail, and Thompson graupel net fluxes near the surface. Conversely, the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions (PSDs) into spectral bins. The results highlight precipitation sensitivity to storm dynamics, fall speed, hydrometeor evolution governed by process rates, and MP PSD design.
2024,
41(5):
801-816.
doi: 10.1007/s00376-023-3060-3
Abstract:
Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts. However, the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known. In this study, a series of forecasts with different forecast lead times for January, April, July, and October of 2018 are conducted over the Beijing-Tianjin-Hebei (BTH) region and the impacts of meteorological forecasting uncertainties on surface PM2.5 concentration forecasts with each lead time are investigated. With increased lead time, the forecasted PM2.5 concentrations significantly change and demonstrate obvious seasonal variations. In general, the forecasting uncertainties in monthly mean surface PM2.5 concentrations in the BTH region due to lead time are the largest (80%) in spring, followed by autumn (~50%), summer (~40%), and winter (20%). In winter, the forecasting uncertainties in total surface PM2.5 mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles. In spring, the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds, thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust. In summer, the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates, which are associated with the reduction of near-surface wind speed and precipitation rate. In autumn, the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles, which is associated with changes in the large-scale circulation.
Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts. However, the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known. In this study, a series of forecasts with different forecast lead times for January, April, July, and October of 2018 are conducted over the Beijing-Tianjin-Hebei (BTH) region and the impacts of meteorological forecasting uncertainties on surface PM2.5 concentration forecasts with each lead time are investigated. With increased lead time, the forecasted PM2.5 concentrations significantly change and demonstrate obvious seasonal variations. In general, the forecasting uncertainties in monthly mean surface PM2.5 concentrations in the BTH region due to lead time are the largest (80%) in spring, followed by autumn (~50%), summer (~40%), and winter (20%). In winter, the forecasting uncertainties in total surface PM2.5 mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles. In spring, the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds, thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust. In summer, the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates, which are associated with the reduction of near-surface wind speed and precipitation rate. In autumn, the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles, which is associated with changes in the large-scale circulation.
2024,
41(5):
817-829.
doi: 10.1007/s00376-023-3012-y
Abstract:
Few studies have investigated the spatial patterns of the air temperature urban heat island (AUHI) and its controlling factors. In this study, the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers. A total of 355 urban clusters were used. We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation. The results show that the midday AUHI is negatively correlated with climate wetness (humid: 0.34 K; semi-humid: 0.50 K; semi-arid: 0.73 K). The annual mean midnight AUHI does not show discernible spatial patterns, but is generally stronger than the midday AUHI. The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid (0.32 ± 0.09 K) and the semi-arid (0.36 ± 0.11 K) climate zones. The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones. The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations. A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.
Few studies have investigated the spatial patterns of the air temperature urban heat island (AUHI) and its controlling factors. In this study, the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers. A total of 355 urban clusters were used. We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation. The results show that the midday AUHI is negatively correlated with climate wetness (humid: 0.34 K; semi-humid: 0.50 K; semi-arid: 0.73 K). The annual mean midnight AUHI does not show discernible spatial patterns, but is generally stronger than the midday AUHI. The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid (0.32 ± 0.09 K) and the semi-arid (0.36 ± 0.11 K) climate zones. The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones. The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations. A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.
2024,
41(5):
830-846.
doi: 10.1007/s00376-023-3094-6
Abstract:
This study compares the summer atmospheric water cycle, including moisture sources and consumption, in the upstream, midstream, and downstream regions of the Yarlung Zangbo River Basin in the southern Tibetan Plateau. The evolutions of moisture properties under the influence of the westerly and summer southerly monsoon are examined using 5-yr multi-source measurements and ERA5 reanalysis data. Note that moisture consumption in this study is associated with clouds, precipitation, and diabatic heating. Compared to the midstream and downstream regions, the upstream region has less moisture, clouds, and precipitation, where the moisture is brought by the westerly. In early August, the vertical wet advection over this region becomes enhanced and generates more high clouds and precipitation. The midstream region has moisture carried by the westerly in June and by the southerly monsoon from July to August. The higher vertical wet advection maximum here forms more high clouds, with a precipitation peak in early July. The downstream region is mainly affected by the southerly-driven wet advection. The rich moisture and strong vertical wet advection here produce the most clouds and precipitation among the three regions, with a precipitation peak in late June. The height of the maximum moisture condensation is different between the midstream region (325 hPa) and the other two regions (375 hPa), due to the higher upward motion maximum in the midstream region. The diabatic heating structures show that stratiform clouds dominate the upstream region, stratiform clouds and deep convection co-exist in the midstream region, and deep convection systems characterize the downstream region.
This study compares the summer atmospheric water cycle, including moisture sources and consumption, in the upstream, midstream, and downstream regions of the Yarlung Zangbo River Basin in the southern Tibetan Plateau. The evolutions of moisture properties under the influence of the westerly and summer southerly monsoon are examined using 5-yr multi-source measurements and ERA5 reanalysis data. Note that moisture consumption in this study is associated with clouds, precipitation, and diabatic heating. Compared to the midstream and downstream regions, the upstream region has less moisture, clouds, and precipitation, where the moisture is brought by the westerly. In early August, the vertical wet advection over this region becomes enhanced and generates more high clouds and precipitation. The midstream region has moisture carried by the westerly in June and by the southerly monsoon from July to August. The higher vertical wet advection maximum here forms more high clouds, with a precipitation peak in early July. The downstream region is mainly affected by the southerly-driven wet advection. The rich moisture and strong vertical wet advection here produce the most clouds and precipitation among the three regions, with a precipitation peak in late June. The height of the maximum moisture condensation is different between the midstream region (325 hPa) and the other two regions (375 hPa), due to the higher upward motion maximum in the midstream region. The diabatic heating structures show that stratiform clouds dominate the upstream region, stratiform clouds and deep convection co-exist in the midstream region, and deep convection systems characterize the downstream region.
2024,
41(5):
847-863.
doi: 10.1007/s00376-023-3033-6
Abstract:
An extreme rainfall event occurred over Hangzhou, China, during the afternoon hours on 24 June 2013. This event occurred under suitable synoptic conditions and the maximum 4-h cumulative rainfall amount was over 150 mm. This rainfall event had two major rainbands. One was caused by a quasi-stationary convective line, and the other by a back-building convective line related to the interaction of the outflow boundary from the first rainband and an existing low-level mesoscale convergence line associated with a mei-yu frontal system. The rainfall event lasted 4 h, while the back-building process occurred in 2 h when the extreme rainfall center formed. So far, few studies have examined the back-building processes in the mei-yu season that are caused by the interaction of a mesoscale convergence line and a convective cold pool. The two rainbands are successfully reproduced by the Weather Research and Forecasting (WRF) model with four-level, two-way interactive nesting. In the model, new cells repeatedly occur at the west side of older cells, and the back-building process occurs in an environment with large CAPE, a low LFC, and plenty of water vapor. Outflows from older cells enhance the low-level convergence that forces new cells. High precipitation efficiency of the back-building training cells leads to accumulated precipitation of over 150 mm. Sensitivity experiments without evaporation of rainwater show that the convective cold pool plays an important role in the organization of the back-building process in the current extreme precipitation case.
An extreme rainfall event occurred over Hangzhou, China, during the afternoon hours on 24 June 2013. This event occurred under suitable synoptic conditions and the maximum 4-h cumulative rainfall amount was over 150 mm. This rainfall event had two major rainbands. One was caused by a quasi-stationary convective line, and the other by a back-building convective line related to the interaction of the outflow boundary from the first rainband and an existing low-level mesoscale convergence line associated with a mei-yu frontal system. The rainfall event lasted 4 h, while the back-building process occurred in 2 h when the extreme rainfall center formed. So far, few studies have examined the back-building processes in the mei-yu season that are caused by the interaction of a mesoscale convergence line and a convective cold pool. The two rainbands are successfully reproduced by the Weather Research and Forecasting (WRF) model with four-level, two-way interactive nesting. In the model, new cells repeatedly occur at the west side of older cells, and the back-building process occurs in an environment with large CAPE, a low LFC, and plenty of water vapor. Outflows from older cells enhance the low-level convergence that forces new cells. High precipitation efficiency of the back-building training cells leads to accumulated precipitation of over 150 mm. Sensitivity experiments without evaporation of rainwater show that the convective cold pool plays an important role in the organization of the back-building process in the current extreme precipitation case.
2024,
41(5):
864-880.
doi: 10.1007/s00376-023-3082-x
Abstract:
A previously developed hybrid coupled model (HCM) is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model (AGCM), denoted as HCMAGCM. In this study, different El Niño flavors, namely the Eastern-Pacific (EP) and Central-Pacific (CP) types, and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM. The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific, including the amplitude and spatial patterns of sea surface temperature (SST), zonal wind stress, and precipitation anomalies. An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events, respectively. Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events, the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter. In particular, the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere, while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American (PNA) pattern. As a result, different climatic impacts exist in North American regions, with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño, respectively. This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.
A previously developed hybrid coupled model (HCM) is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model (AGCM), denoted as HCMAGCM. In this study, different El Niño flavors, namely the Eastern-Pacific (EP) and Central-Pacific (CP) types, and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM. The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific, including the amplitude and spatial patterns of sea surface temperature (SST), zonal wind stress, and precipitation anomalies. An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events, respectively. Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events, the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter. In particular, the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere, while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American (PNA) pattern. As a result, different climatic impacts exist in North American regions, with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño, respectively. This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.
2024,
41(5):
881-893.
doi: 10.1007/s00376-023-3093-7
Abstract:
This study investigates the activity of tropical cyclones (TCs) in the Bay of Bengal (BOB) from 1979 to 2018 to discover the mechanism affecting the contribution rate to the meridional moisture budget anomaly (MMBA) over the southern boundary of the Tibetan Plateau (SBTP). May and October–December are the bimodal phases of BOB TC frequency, which decreases month by month from October to December and is relatively low in May. However, the contribution rate to the MMBA is the highest in May. The seasonal variation in the meridional position of the westerlies is the key factor affecting the contribution rate. The relatively southern (northern) position of the westerlies in November and December (May) results in a lower (higher) contribution rate to the MMBA. This mechanism is confirmed by the momentum equation. When water vapor enters the westerlies near the trough line, the resultant meridional acceleration is directed north. It follows that the farther north the trough is, and the farther north the water vapor can be transported. When water vapor enters the westerlies from the area near the ridge line, for Type-T (Type-R) TCs, water vapor enters the westerlies downstream of the trough (ridge). Consequently, the direction of the resultant meridional acceleration is directed south and the resultant zonal acceleration is directed east (west), which is not conducive to the northward transport of water vapor. This is especially the case if the trough or ridge is relatively south, as the water vapor may not cross the SBTP.
This study investigates the activity of tropical cyclones (TCs) in the Bay of Bengal (BOB) from 1979 to 2018 to discover the mechanism affecting the contribution rate to the meridional moisture budget anomaly (MMBA) over the southern boundary of the Tibetan Plateau (SBTP). May and October–December are the bimodal phases of BOB TC frequency, which decreases month by month from October to December and is relatively low in May. However, the contribution rate to the MMBA is the highest in May. The seasonal variation in the meridional position of the westerlies is the key factor affecting the contribution rate. The relatively southern (northern) position of the westerlies in November and December (May) results in a lower (higher) contribution rate to the MMBA. This mechanism is confirmed by the momentum equation. When water vapor enters the westerlies near the trough line, the resultant meridional acceleration is directed north. It follows that the farther north the trough is, and the farther north the water vapor can be transported. When water vapor enters the westerlies from the area near the ridge line, for Type-T (Type-R) TCs, water vapor enters the westerlies downstream of the trough (ridge). Consequently, the direction of the resultant meridional acceleration is directed south and the resultant zonal acceleration is directed east (west), which is not conducive to the northward transport of water vapor. This is especially the case if the trough or ridge is relatively south, as the water vapor may not cross the SBTP.
2024,
41(5):
894-914.
doi: 10.1007/s00376-023-3127-1
Abstract:
The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation (QBO) during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset (CRA-40) is evaluated by comparing two widely used reanalysis datasets, ERA-5 and MERRA-2. CRA-40 demonstrates a comparable performance with ERA-5 and MERRA-2 in characterizing the winter and spring circulation in the lower and middle Arctic stratosphere. Specifically, differences in the climatological polar-mean temperature and polar night jet among the three reanalyses are within ±0.5 K and ±0.5 m s–1, respectively. The onset dates of the stratospheric sudden warming and stratospheric final warming events at 10 hPa in CRA-40, together with the dynamics and circulation anomalies during the onset process of warming events, are nearly identical to the other two reanalyses with slight differences. By contrast, the CRA-40 dataset demonstrates a deteriorated performance in describing the QBO below 10 hPa compared to the other two reanalysis products, manifested by the larger easterly biases of the QBO index, the remarkably weaker amplitude of the QBO, and the weaker wavelet power of the QBO period. Such pronounced biases are mainly concentrated in the period 1981–98 and largely reduced by at least 39% in 1999–2019. Thus, particular caution is needed in studying the QBO based on CRA-40. All three reanalyses exhibit greater disagreement in the upper stratosphere compared to the lower and middle stratosphere for both the polar region and the tropics.
The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation (QBO) during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset (CRA-40) is evaluated by comparing two widely used reanalysis datasets, ERA-5 and MERRA-2. CRA-40 demonstrates a comparable performance with ERA-5 and MERRA-2 in characterizing the winter and spring circulation in the lower and middle Arctic stratosphere. Specifically, differences in the climatological polar-mean temperature and polar night jet among the three reanalyses are within ±0.5 K and ±0.5 m s–1, respectively. The onset dates of the stratospheric sudden warming and stratospheric final warming events at 10 hPa in CRA-40, together with the dynamics and circulation anomalies during the onset process of warming events, are nearly identical to the other two reanalyses with slight differences. By contrast, the CRA-40 dataset demonstrates a deteriorated performance in describing the QBO below 10 hPa compared to the other two reanalysis products, manifested by the larger easterly biases of the QBO index, the remarkably weaker amplitude of the QBO, and the weaker wavelet power of the QBO period. Such pronounced biases are mainly concentrated in the period 1981–98 and largely reduced by at least 39% in 1999–2019. Thus, particular caution is needed in studying the QBO based on CRA-40. All three reanalyses exhibit greater disagreement in the upper stratosphere compared to the lower and middle stratosphere for both the polar region and the tropics.
2024,
41(5):
915-936.
doi: 10.1007/s00376-023-3034-5
Abstract:
Based on hourly rain gauge data during May–September of 2016–20, we analyze the spatiotemporal 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 terrain (i.e., mountain, foothill, and plain), the amount of TR and SDHR both maximize in June/July, and the contribution of SDHR to TR (CST) peaks 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 over the mountains and in the 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 terrain, the 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 of TR and SDHR in the foothills is larger than over the mountains and plains. The TR intensity in the foothills increases significantly from midnight to afternoon, suggesting that thermal instability may play an important role in this process.
Based on hourly rain gauge data during May–September of 2016–20, we analyze the spatiotemporal 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 terrain (i.e., mountain, foothill, and plain), the amount of TR and SDHR both maximize in June/July, and the contribution of SDHR to TR (CST) peaks 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 over the mountains and in the 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 terrain, the 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 of TR and SDHR in the foothills is larger than over the mountains and plains. The TR intensity in the foothills increases significantly from midnight to afternoon, suggesting that thermal instability may play an important role in this process.
2024,
41(5):
937-958.
doi: 10.1007/s00376-023-3072-z
Abstract:
This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager (AGRI) radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation (DA) method along with the WRF model. A channel-sensitive cloud detection scheme based on the particle filter (PF) algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual (MMR) algorithm and another traditional cloud mask–dependent cloud detection scheme. Results show that both channel-sensitive cloud detection schemes are effective, while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel. In general, the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances. Moreover, it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon, including the temperature, moisture, and dynamical conditions. The typhoon track forecast skill is improved with AGRI radiance DA, which could be explained by better simulating the upper trough. The impact of assimilating AGRI radiances on typhoon intensity forecasts is small. On the other hand, improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields, albeit the improvements are limited.
This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager (AGRI) radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation (DA) method along with the WRF model. A channel-sensitive cloud detection scheme based on the particle filter (PF) algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual (MMR) algorithm and another traditional cloud mask–dependent cloud detection scheme. Results show that both channel-sensitive cloud detection schemes are effective, while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel. In general, the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances. Moreover, it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon, including the temperature, moisture, and dynamical conditions. The typhoon track forecast skill is improved with AGRI radiance DA, which could be explained by better simulating the upper trough. The impact of assimilating AGRI radiances on typhoon intensity forecasts is small. On the other hand, improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields, albeit the improvements are limited.
2024,
41(5):
959-973.
doi: 10.1007/s00376-023-3111-9
Abstract:
The spring snow cover (SC) over the western Tibetan Plateau (TP) (TPSC) (W_TPSC) and eastern TPSC (E_TPSC) have displayed remarkable decreasing and increasing trends, respectively, during 1985–2020. The current work investigates the possible mechanisms accounting for these distinct TPSC changes. Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures, while the increase in E_TPSC is closely linked to enhanced precipitation. Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP. The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP. Conversely, anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific, leading to an increase in snowfall over the eastern TP. Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions. Springtime warming of the subtropical North Atlantic (NA) sea surface temperature (SST) induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP. Furthermore, the decline in winter sea ice (SIC) over the Barents Sea exerts a persistent warming influence on the atmosphere, inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring. Additionally, an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia, which further promotes more snowfall over eastern TP.
The spring snow cover (SC) over the western Tibetan Plateau (TP) (TPSC) (W_TPSC) and eastern TPSC (E_TPSC) have displayed remarkable decreasing and increasing trends, respectively, during 1985–2020. The current work investigates the possible mechanisms accounting for these distinct TPSC changes. Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures, while the increase in E_TPSC is closely linked to enhanced precipitation. Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP. The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP. Conversely, anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific, leading to an increase in snowfall over the eastern TP. Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions. Springtime warming of the subtropical North Atlantic (NA) sea surface temperature (SST) induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP. Furthermore, the decline in winter sea ice (SIC) over the Barents Sea exerts a persistent warming influence on the atmosphere, inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring. Additionally, an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia, which further promotes more snowfall over eastern TP.
2024,
41(5):
974-988.
doi: 10.1007/s00376-023-3101-y
Abstract:
In this study, we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model (GCM) data to drive a regional climate model (RCM) over the Asia-western North Pacific region. Three simulations were conducted with a 25-km grid spacing for the period 1980–2014. The first simulation (WRF_ERA5) was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset and served as the validation dataset. The original GCM dataset (MPI-ESM1-2-HR model) was used to drive the second simulation (WRF_GCM), while the third simulation (WRF_GCMbc) was driven by the bias-corrected GCM dataset. The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models. Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors (RMSEs) of the climatological mean of downscaled variables, including temperature, precipitation, snow, wind, relative humidity, and planetary boundary layer height by 50%–90% compared to the WRF_GCM. Similarly, the RMSEs of interannual-to-interdecadal variances of downscaled variables were reduced by 30%–60%. Furthermore, the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities. The leading empirical orthogonal function (EOF) shows a monopole precipitation mode in the WRF_GCM. In contrast, the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China. This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.
In this study, we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model (GCM) data to drive a regional climate model (RCM) over the Asia-western North Pacific region. Three simulations were conducted with a 25-km grid spacing for the period 1980–2014. The first simulation (WRF_ERA5) was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset and served as the validation dataset. The original GCM dataset (MPI-ESM1-2-HR model) was used to drive the second simulation (WRF_GCM), while the third simulation (WRF_GCMbc) was driven by the bias-corrected GCM dataset. The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models. Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors (RMSEs) of the climatological mean of downscaled variables, including temperature, precipitation, snow, wind, relative humidity, and planetary boundary layer height by 50%–90% compared to the WRF_GCM. Similarly, the RMSEs of interannual-to-interdecadal variances of downscaled variables were reduced by 30%–60%. Furthermore, the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities. The leading empirical orthogonal function (EOF) shows a monopole precipitation mode in the WRF_GCM. In contrast, the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China. This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.
2024,
41(5):
989-1000.
doi: 10.1007/s00376-023-3089-3
Abstract:
Understanding the response of the Earth system to varying concentrations of carbon dioxide (CO2) is critical for projecting possible future climate change and for providing insight into mitigation and adaptation strategies in the near future. In this study, we generate a dataset by conducting an experiment involving carbon dioxide removal (CDR)—a potential way to suppress global warming—using the Chinese Academy of Sciences Earth System Model version 2.0 (CAS-ESM2.0). A preliminary evaluation is provided. The model is integrated from 200–340 years as a 1% yr−1 CO2 concentration increase experiment, and then to ~478 years as a carbon dioxide removal experiment until CO2 returns to its original value. Finally, another 80 years is integrated in which CO2 is kept constant. Changes in the 2-m temperature, precipitation, sea surface temperature, ocean temperature, Atlantic meridional overturning circulation (AMOC), and sea surface height are all analyzed. In the ramp-up period, the global mean 2-m temperature and precipitation both increase while the AMOC weakens. Values of all the above variables change in the opposite direction in the ramp-down period, with a delayed peak relative to the CO2 peak. After CO2 returns to its original value, the global mean 2-m temperature is still ~1 K higher than in the original state, and precipitation is ~0.07 mm d–1 higher. At the end of the simulation, there is a ~0.5°C increase in ocean temperature and a 1 Sv weakening of the AMOC. Our model simulation produces similar results to those of comparable experiments previously reported in the literature.
Understanding the response of the Earth system to varying concentrations of carbon dioxide (CO2) is critical for projecting possible future climate change and for providing insight into mitigation and adaptation strategies in the near future. In this study, we generate a dataset by conducting an experiment involving carbon dioxide removal (CDR)—a potential way to suppress global warming—using the Chinese Academy of Sciences Earth System Model version 2.0 (CAS-ESM2.0). A preliminary evaluation is provided. The model is integrated from 200–340 years as a 1% yr−1 CO2 concentration increase experiment, and then to ~478 years as a carbon dioxide removal experiment until CO2 returns to its original value. Finally, another 80 years is integrated in which CO2 is kept constant. Changes in the 2-m temperature, precipitation, sea surface temperature, ocean temperature, Atlantic meridional overturning circulation (AMOC), and sea surface height are all analyzed. In the ramp-up period, the global mean 2-m temperature and precipitation both increase while the AMOC weakens. Values of all the above variables change in the opposite direction in the ramp-down period, with a delayed peak relative to the CO2 peak. After CO2 returns to its original value, the global mean 2-m temperature is still ~1 K higher than in the original state, and precipitation is ~0.07 mm d–1 higher. At the end of the simulation, there is a ~0.5°C increase in ocean temperature and a 1 Sv weakening of the AMOC. Our model simulation produces similar results to those of comparable experiments previously reported in the literature.
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