2022 Vol. 39, No. 6
Display Method:
2022, 39(6): 1-1.
Abstract:
2022, 39(6): 819-860.
doi: 10.1007/s00376-021-1371-9
Abstract:
Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.
Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.
2022, 39(6): 861-875.
doi: 10.1007/s00376-021-1281-x
Abstract:
Estimating the impacts on PM2.5 pollution and CO2 emissions by human activities in different urban regions is important for developing efficient policies. In early 2020, China implemented a lockdown policy to contain the spread of COVID-19, resulting in a significant reduction of human activities. This event presents a convenient opportunity to study the impact of human activities in the transportation and industrial sectors on air pollution. Here, we investigate the variations in air quality attributed to the COVID-19 lockdown policy in the megacities of China by combining in-situ environmental and meteorological datasets, the Suomi-NPP/VIIRS and the CO2 emissions from the Carbon Monitor project. Our study shows that PM2.5 concentrations in the spring of 2020 decreased by 41.87% in the Yangtze River Delta (YRD) and 43.30% in the Pearl River Delta (PRD), respectively, owing to the significant shutdown of traffic and manufacturing industries. However, PM2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region only decreased by 2.01% because the energy and steel industries were not fully paused. In addition, unfavorable weather conditions contributed to further increases in the PM2.5 concentration. Furthermore, CO2 concentrations were not significantly affected in China during the short-term emission reduction, despite a 19.52% reduction in CO2 emissions compared to the same period in 2019. Our results suggest that concerted efforts from different emission sectors and effective long-term emission reduction strategies are necessary to control air pollution and CO2 emissions.
Estimating the impacts on PM2.5 pollution and CO2 emissions by human activities in different urban regions is important for developing efficient policies. In early 2020, China implemented a lockdown policy to contain the spread of COVID-19, resulting in a significant reduction of human activities. This event presents a convenient opportunity to study the impact of human activities in the transportation and industrial sectors on air pollution. Here, we investigate the variations in air quality attributed to the COVID-19 lockdown policy in the megacities of China by combining in-situ environmental and meteorological datasets, the Suomi-NPP/VIIRS and the CO2 emissions from the Carbon Monitor project. Our study shows that PM2.5 concentrations in the spring of 2020 decreased by 41.87% in the Yangtze River Delta (YRD) and 43.30% in the Pearl River Delta (PRD), respectively, owing to the significant shutdown of traffic and manufacturing industries. However, PM2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region only decreased by 2.01% because the energy and steel industries were not fully paused. In addition, unfavorable weather conditions contributed to further increases in the PM2.5 concentration. Furthermore, CO2 concentrations were not significantly affected in China during the short-term emission reduction, despite a 19.52% reduction in CO2 emissions compared to the same period in 2019. Our results suggest that concerted efforts from different emission sectors and effective long-term emission reduction strategies are necessary to control air pollution and CO2 emissions.
2022, 39(6): 876-888.
doi: 10.1007/s00376-021-1244-2
Abstract:
Variations in wave energy and amplitude for Rossby waves are investigated by solving the wave energy equation for the quasigeostrophic barotropic potential vorticity model. The results suggest that compared with rays in the nondivergent barotropic model, rays in the divergent model can have enhanced meridional and zonal propagation, accompanied by a more dramatic variability in both wave energy and amplitude, which is caused by introducing the divergence effect of the free surface in the quasigeostrophic model. For rays propagating in a region enclosed by a turning latitude and a critical latitude, the wave energy approaches the maximum value inside the region, while the amplitude approaches the maximum at the turning latitude. Waves can develop when both the wave energy and amplitude increase. For rays propagating in a region enclosed by two turning latitudes, the wave energy approaches the minimum value at one turning latitude and the maximum value at the other latitude, while the total wavenumber approaches the maximum value inside the region. The resulting amplitude increases if the total wavenumber decreases or the wave energy increases more significantly and decreases if the total wavenumber increases or the wave energy decreases more significantly. The matched roles of the energy from the basic flow and the divergence of the group velocity contribute to the slightly oscillating wave energy, which causes a slightly oscillating amplitude as well as the slightly oscillating total wavenumber.
Variations in wave energy and amplitude for Rossby waves are investigated by solving the wave energy equation for the quasigeostrophic barotropic potential vorticity model. The results suggest that compared with rays in the nondivergent barotropic model, rays in the divergent model can have enhanced meridional and zonal propagation, accompanied by a more dramatic variability in both wave energy and amplitude, which is caused by introducing the divergence effect of the free surface in the quasigeostrophic model. For rays propagating in a region enclosed by a turning latitude and a critical latitude, the wave energy approaches the maximum value inside the region, while the amplitude approaches the maximum at the turning latitude. Waves can develop when both the wave energy and amplitude increase. For rays propagating in a region enclosed by two turning latitudes, the wave energy approaches the minimum value at one turning latitude and the maximum value at the other latitude, while the total wavenumber approaches the maximum value inside the region. The resulting amplitude increases if the total wavenumber decreases or the wave energy increases more significantly and decreases if the total wavenumber increases or the wave energy decreases more significantly. The matched roles of the energy from the basic flow and the divergence of the group velocity contribute to the slightly oscillating wave energy, which causes a slightly oscillating amplitude as well as the slightly oscillating total wavenumber.
2022, 39(6): 889-902.
doi: 10.1007/s00376-021-1368-4
Abstract:
El Niño-Southern Oscillation (ENSO) can be currently predicted reasonably well six months and longer, but large biases and uncertainties remain in its real-time prediction. Various approaches have been taken to improve understanding of ENSO processes, and different models for ENSO predictions have been developed, including linear statistical models based on principal oscillation pattern (POP) analyses, convolutional neural networks (CNNs), and so on. Here, we develop a novel hybrid model, named as POP-Net, by combining the POP analysis procedure with CNN-long short-term memory (LSTM) algorithm to predict the Niño-3.4 sea surface temperature (SST) index. ENSO predictions are compared with each other from the corresponding three models: POP model, CNN-LSTM model, and POP-Net, respectively. The POP-based pre-processing acts to enhance ENSO-related signals of interest while filtering unrelated noise. Consequently, an improved prediction is achieved in the POP-Net relative to others. The POP-Net shows a high-correlation skill for 17-month lead time prediction (correlation coefficients exceeding 0.5) during the 1994–2020 validation period. The POP-Net also alleviates the spring predictability barrier (SPB). It is concluded that value-added artificial neural networks for improved ENSO predictions are possible by including the process-oriented analyses to enhance signal representations.
El Niño-Southern Oscillation (ENSO) can be currently predicted reasonably well six months and longer, but large biases and uncertainties remain in its real-time prediction. Various approaches have been taken to improve understanding of ENSO processes, and different models for ENSO predictions have been developed, including linear statistical models based on principal oscillation pattern (POP) analyses, convolutional neural networks (CNNs), and so on. Here, we develop a novel hybrid model, named as POP-Net, by combining the POP analysis procedure with CNN-long short-term memory (LSTM) algorithm to predict the Niño-3.4 sea surface temperature (SST) index. ENSO predictions are compared with each other from the corresponding three models: POP model, CNN-LSTM model, and POP-Net, respectively. The POP-based pre-processing acts to enhance ENSO-related signals of interest while filtering unrelated noise. Consequently, an improved prediction is achieved in the POP-Net relative to others. The POP-Net shows a high-correlation skill for 17-month lead time prediction (correlation coefficients exceeding 0.5) during the 1994–2020 validation period. The POP-Net also alleviates the spring predictability barrier (SPB). It is concluded that value-added artificial neural networks for improved ENSO predictions are possible by including the process-oriented analyses to enhance signal representations.
2022, 39(6): 903-926.
doi: 10.1007/s00376-021-1153-4
Abstract:
The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979–2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are examined by comparison with observational and reanalysis datasets. Most of the models reasonably represent the Beaufort Gyre (BG) and Transpolar Drift Stream (TDS) in the spatial patterns of their long-term mean sea ice drift, while the detailed location, extent, and strength of the BG and TDS vary among the models. About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern. About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern. In the observation/reanalysis, however, the sea ice drift pattern does not match well with the surface ocean current pattern. All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic. For the Arctic basin-wide spatial average, five of the nine models overestimate the Arctic long-term (1979–2014) mean sea ice drift speed in all months. Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn. The increases are weaker than those in the observation. This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.
The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979–2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are examined by comparison with observational and reanalysis datasets. Most of the models reasonably represent the Beaufort Gyre (BG) and Transpolar Drift Stream (TDS) in the spatial patterns of their long-term mean sea ice drift, while the detailed location, extent, and strength of the BG and TDS vary among the models. About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern. About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern. In the observation/reanalysis, however, the sea ice drift pattern does not match well with the surface ocean current pattern. All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic. For the Arctic basin-wide spatial average, five of the nine models overestimate the Arctic long-term (1979–2014) mean sea ice drift speed in all months. Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn. The increases are weaker than those in the observation. This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.
2022, 39(6): 927-942.
doi: 10.1007/s00376-021-1263-z
Abstract:
The 2015/16 El Niño displayed a distinct feature in the SST anomalies over the far eastern Pacific (FEP) compared to the 1997/98 extreme case. In contrast to the strong warm SST anomalies in the FEP in the 1997/98 event, the FEP warm SST anomalies in the 2015/16 El Niño were modest and accompanied by strong southeasterly wind anomalies in the southeastern Pacific. Exploring possible underlying causes of this distinct difference in the FEP may improve understanding of the diversity of extreme El Niños. Here, we employ observational analyses and numerical model experiments to tackle this issue. Mixed-layer heat budget analysis suggests that compared to the 1997/98 event, the modest FEP SST warming in the 2015/16 event was closely related to strong vertical upwelling, strong westward current, and enhanced surface evaporation, which were caused by the strong southeasterly wind anomalies in the southeastern Pacific. The strong southeasterly wind anomalies were initially triggered by the combined effects of warm SST anomalies in the equatorial central and eastern Pacific (CEP) and cold SST anomalies in the southeastern subtropical Pacific in the antecedent winter, and then sustained by the warm SST anomalies over the northeastern subtropical Pacific and CEP. In contrast, southeasterly wind anomalies in the 1997/98 El Niño were partly restrained by strong anomalously negative sea level pressure and northwesterlies in the northeast flank of the related anomalous cyclone in the subtropical South Pacific. In addition, the strong southeasterly wind and modest SST anomalies in the 2015/16 El Niño may also have been partly related to decadal climate variability.
The 2015/16 El Niño displayed a distinct feature in the SST anomalies over the far eastern Pacific (FEP) compared to the 1997/98 extreme case. In contrast to the strong warm SST anomalies in the FEP in the 1997/98 event, the FEP warm SST anomalies in the 2015/16 El Niño were modest and accompanied by strong southeasterly wind anomalies in the southeastern Pacific. Exploring possible underlying causes of this distinct difference in the FEP may improve understanding of the diversity of extreme El Niños. Here, we employ observational analyses and numerical model experiments to tackle this issue. Mixed-layer heat budget analysis suggests that compared to the 1997/98 event, the modest FEP SST warming in the 2015/16 event was closely related to strong vertical upwelling, strong westward current, and enhanced surface evaporation, which were caused by the strong southeasterly wind anomalies in the southeastern Pacific. The strong southeasterly wind anomalies were initially triggered by the combined effects of warm SST anomalies in the equatorial central and eastern Pacific (CEP) and cold SST anomalies in the southeastern subtropical Pacific in the antecedent winter, and then sustained by the warm SST anomalies over the northeastern subtropical Pacific and CEP. In contrast, southeasterly wind anomalies in the 1997/98 El Niño were partly restrained by strong anomalously negative sea level pressure and northwesterlies in the northeast flank of the related anomalous cyclone in the subtropical South Pacific. In addition, the strong southeasterly wind and modest SST anomalies in the 2015/16 El Niño may also have been partly related to decadal climate variability.
2022, 39(6): 943-952.
doi: 10.1007/s00376-021-1364-8
Abstract:
Traditionally, a delayed (early) onset of the South China Sea summer monsoon (SCSSM) has been observed to follow a warm (cold) El Niño-Southern Oscillation (ENSO) event in winter, supporting high seasonal predictability of SCSSM onset. However, the empirical seasonal forecasting skill of the SCSSM onset, solely based on ENSO, has deteriorated since 2010. Meanwhile, unexpected delayed onsets of the SCSSM have also occurred in the past decade. We attribute these changes to the Northwest Indian Ocean (NWIO) warming of the sea surface. The NWIO warming has teleconnections related to (1) suppressing the seasonal convection over the South China Sea, which weakens the impacts of ENSO on SCSSM onset and delays the start of SCSSM, and (2) favoring more high-frequency, propagating moist convective activities, which enhances the uncertainty of the seasonal prediction of SCSSM onset date. Our results yield insight into the predictability of the SCSSM onset under the context of uneven ocean warming operating within the larger-scale background state of global climate change.
Traditionally, a delayed (early) onset of the South China Sea summer monsoon (SCSSM) has been observed to follow a warm (cold) El Niño-Southern Oscillation (ENSO) event in winter, supporting high seasonal predictability of SCSSM onset. However, the empirical seasonal forecasting skill of the SCSSM onset, solely based on ENSO, has deteriorated since 2010. Meanwhile, unexpected delayed onsets of the SCSSM have also occurred in the past decade. We attribute these changes to the Northwest Indian Ocean (NWIO) warming of the sea surface. The NWIO warming has teleconnections related to (1) suppressing the seasonal convection over the South China Sea, which weakens the impacts of ENSO on SCSSM onset and delays the start of SCSSM, and (2) favoring more high-frequency, propagating moist convective activities, which enhances the uncertainty of the seasonal prediction of SCSSM onset date. Our results yield insight into the predictability of the SCSSM onset under the context of uneven ocean warming operating within the larger-scale background state of global climate change.
2022, 39(6): 953-966.
doi: 10.1007/s00376-021-1358-6
Abstract:
Ocean spiciness is referred to as density-compensated temperature and salinity variations with warm (cool) and salty (fresh) waters having high (low) spiciness, respectively. The structure and evolution of density-compensated (warm/salty or cool/fresh) spiciness anomalies are investigated in the North Pacific thermocline using Argo observations during the period 2004–20. Two well-organized decadal spiciness events are identified through isopycnal surface analyses. One warm/salty spiciness anomaly of about 0.15°C and 0.05 g kg−1 temperature and salinity perturbations on the 25 kg m−3 isopycnal surface appeared in the eastern subtropical North Pacific at (18°–30°N, 120°–150°W) in 2007, which then migrated southwestward along the mean circulation and arrived in the western tropics at (~15°N, 145°E–175°W) in 2012–13, with the reduced salinity perturbation of about 0.043 g kg−1. Another cool/fresh spiciness anomaly of about −0.2°C and −0.07 g kg−1 temperature and salinity perturbations originated from the eastern subtropics at (120°–150°W, ~30°N) in 2014 and followed a similar advective pathway during the period from 2014–15 to 2019–20. The subduction pathway can be adequately determined by the mean Montgomery stream function on the isopycnal surface; the propagation direction and speed are in good agreement with the expectation for the role played by advection due to the mean geostrophic current. Moreover, the subducted decadal spiciness anomalies can have negative feedback on sea surface temperature (SST) variability in the western tropical Pacific through the diapycnal processes. The identifications of these density-compensated spiciness anomalies and their propagation pathways provide a clear illustration of the oceanic extratropics-tropics interactions in the North Pacific Ocean.
Ocean spiciness is referred to as density-compensated temperature and salinity variations with warm (cool) and salty (fresh) waters having high (low) spiciness, respectively. The structure and evolution of density-compensated (warm/salty or cool/fresh) spiciness anomalies are investigated in the North Pacific thermocline using Argo observations during the period 2004–20. Two well-organized decadal spiciness events are identified through isopycnal surface analyses. One warm/salty spiciness anomaly of about 0.15°C and 0.05 g kg−1 temperature and salinity perturbations on the 25 kg m−3 isopycnal surface appeared in the eastern subtropical North Pacific at (18°–30°N, 120°–150°W) in 2007, which then migrated southwestward along the mean circulation and arrived in the western tropics at (~15°N, 145°E–175°W) in 2012–13, with the reduced salinity perturbation of about 0.043 g kg−1. Another cool/fresh spiciness anomaly of about −0.2°C and −0.07 g kg−1 temperature and salinity perturbations originated from the eastern subtropics at (120°–150°W, ~30°N) in 2014 and followed a similar advective pathway during the period from 2014–15 to 2019–20. The subduction pathway can be adequately determined by the mean Montgomery stream function on the isopycnal surface; the propagation direction and speed are in good agreement with the expectation for the role played by advection due to the mean geostrophic current. Moreover, the subducted decadal spiciness anomalies can have negative feedback on sea surface temperature (SST) variability in the western tropical Pacific through the diapycnal processes. The identifications of these density-compensated spiciness anomalies and their propagation pathways provide a clear illustration of the oceanic extratropics-tropics interactions in the North Pacific Ocean.
2022, 39(6): 967-984.
doi: 10.1007/s00376-021-1383-5
Abstract:
Moisture contribution and transport pathways for Central Asia (CA) are quantitatively examined using the Lagrangian water cycle model based on reanalysis and observational data to explain the precipitation seasonality and the moisture transport variation during 1979–2015. Westerly-related (northwesterly and westerly) transport explains 42% of CA precipitation and dominates in southwest CA, where precipitation is greatest in the cold season. Southeast CA, including part of Northwest China, experiences its maximum precipitation in the warm season and is solely dominated by southerly transport, which explains about 48% of CA precipitation. The remaining 10% of CA precipitation is explained by northerly transport, which steadily impacts north CA and causes a maximum in precipitation in the warm season. Most CA areas are exposed to seasonally varying moisture transport, except for southeast and north CA, which are impacted by southerly and northerly transport year-round. In general, the midlatitude westerlies-driven transport and the Indian monsoon-driven southerly-related transport explain most of the spatial differences in precipitation seasonality over CA. Moreover, the contribution ratio of local evaporation in CA to precipitation exhibits significant interdecadal variability and a meridionally oriented tripole of moisture transport anomalies. Since the early 2000s, CA has experienced a decade of anomalously low local moisture contribution, which seems jointly determined by the weakened moisture contribution from midlatitudes (the Atlantic, Europe, and CA itself) and the enhanced contribution from high latitudes (West Siberia and the Arctic) and tropical areas (South Asia and the Indian Ocean).
Moisture contribution and transport pathways for Central Asia (CA) are quantitatively examined using the Lagrangian water cycle model based on reanalysis and observational data to explain the precipitation seasonality and the moisture transport variation during 1979–2015. Westerly-related (northwesterly and westerly) transport explains 42% of CA precipitation and dominates in southwest CA, where precipitation is greatest in the cold season. Southeast CA, including part of Northwest China, experiences its maximum precipitation in the warm season and is solely dominated by southerly transport, which explains about 48% of CA precipitation. The remaining 10% of CA precipitation is explained by northerly transport, which steadily impacts north CA and causes a maximum in precipitation in the warm season. Most CA areas are exposed to seasonally varying moisture transport, except for southeast and north CA, which are impacted by southerly and northerly transport year-round. In general, the midlatitude westerlies-driven transport and the Indian monsoon-driven southerly-related transport explain most of the spatial differences in precipitation seasonality over CA. Moreover, the contribution ratio of local evaporation in CA to precipitation exhibits significant interdecadal variability and a meridionally oriented tripole of moisture transport anomalies. Since the early 2000s, CA has experienced a decade of anomalously low local moisture contribution, which seems jointly determined by the weakened moisture contribution from midlatitudes (the Atlantic, Europe, and CA itself) and the enhanced contribution from high latitudes (West Siberia and the Arctic) and tropical areas (South Asia and the Indian Ocean).
2022, 39(6): 985-998.
doi: 10.1007/s00376-021-1260-2
Abstract:
Cloud-to-ground (CG) lightning data and the ECMWF ERA-Interim reanalysis dataset are analyzed to gain insight into the spatiotemporal distribution and synoptic background of winter-season CG flashes between December 2010 and February 2020 in China. We identify three Winter Lightning Frequent Areas (WLAs): the southwest side of the Yunnan-Guizhou Plateau (WLA1), the east side of the Yunnan-Guizhou Plateau (WLA2), and the Poyang Lake Plain (WLA3). The CG lightning flashes most frequently occur at local midnight and have a monthly peak in February. The CG lightning in WLA1 is mostly generated in non-frontal weather; however, the lightning in WLA2 and WLA3 mostly occurs in frontal systems. The frontal circulation situation is divided into four typical types: transversal trough after high pressure, low vortex, confrontational convergence, and asymptotic convergence. In all typical weather patterns, the lightning occurs downstream of a 500 hPa trough and is accompanied by a southwesterly low-level jet. The convective parameters of winter thunderstorms differ greatly from those of summer thunderstorms. The maximum convective available potential energy (MCAPE) and K-index (KI) are more useful metrics than convective available potential energy (CAPE) and Showalter index (SI) during winter. This study further deepens the understanding of the distribution characteristics of winter CG lightning in China, which motivates further research to improve the ability of winter thunderstorm prediction.
Cloud-to-ground (CG) lightning data and the ECMWF ERA-Interim reanalysis dataset are analyzed to gain insight into the spatiotemporal distribution and synoptic background of winter-season CG flashes between December 2010 and February 2020 in China. We identify three Winter Lightning Frequent Areas (WLAs): the southwest side of the Yunnan-Guizhou Plateau (WLA1), the east side of the Yunnan-Guizhou Plateau (WLA2), and the Poyang Lake Plain (WLA3). The CG lightning flashes most frequently occur at local midnight and have a monthly peak in February. The CG lightning in WLA1 is mostly generated in non-frontal weather; however, the lightning in WLA2 and WLA3 mostly occurs in frontal systems. The frontal circulation situation is divided into four typical types: transversal trough after high pressure, low vortex, confrontational convergence, and asymptotic convergence. In all typical weather patterns, the lightning occurs downstream of a 500 hPa trough and is accompanied by a southwesterly low-level jet. The convective parameters of winter thunderstorms differ greatly from those of summer thunderstorms. The maximum convective available potential energy (MCAPE) and K-index (KI) are more useful metrics than convective available potential energy (CAPE) and Showalter index (SI) during winter. This study further deepens the understanding of the distribution characteristics of winter CG lightning in China, which motivates further research to improve the ability of winter thunderstorm prediction.
2022, 39(6): 999-1011.
doi: 10.1007/s00376-021-1219-3
Abstract:
Rainfall amount in mid-summer (July and August) is much greater over eastern than western Sichuan, which are characterized by basin and plateau, respectively. It is shown that the interannual variations of extreme rainfall over these two regions are roughly independent, and they correspond to distinct anomalies of both large-scale circulation and sea surface temperature (SST). The enhanced extreme rainfall over western Sichuan is associated with a southward shift of the Asian westerly jet, while the enhanced extreme rainfall over eastern Sichuan is associated with an anticyclonic anomaly in the upper troposphere over China. At low levels, on the other hand, the enhanced extreme rainfall over western Sichuan is related to two components of wind anomalies, namely southwesterly over southwestern Sichuan and northeasterly over northeastern Sichuan, which favor more rainfall under the effects of the topography. Relatively speaking, the enhanced extreme rainfall over eastern Sichuan corresponds to the low-level southerly anomalies to the east of Sichuan, which curve into northeasterly anomalies over the basin when they encounter the mountains to the north of the basin. Therefore, it can be concluded that the topography in and around Sichuan plays a crucial role in inducing extreme rainfall both over western and eastern Sichuan. Finally, the enhanced extreme rainfall in western and eastern Sichuan is related to warmer SSTs in the Maritime Continent and cooler SSTs in the equatorial central Pacific, respectively.
Rainfall amount in mid-summer (July and August) is much greater over eastern than western Sichuan, which are characterized by basin and plateau, respectively. It is shown that the interannual variations of extreme rainfall over these two regions are roughly independent, and they correspond to distinct anomalies of both large-scale circulation and sea surface temperature (SST). The enhanced extreme rainfall over western Sichuan is associated with a southward shift of the Asian westerly jet, while the enhanced extreme rainfall over eastern Sichuan is associated with an anticyclonic anomaly in the upper troposphere over China. At low levels, on the other hand, the enhanced extreme rainfall over western Sichuan is related to two components of wind anomalies, namely southwesterly over southwestern Sichuan and northeasterly over northeastern Sichuan, which favor more rainfall under the effects of the topography. Relatively speaking, the enhanced extreme rainfall over eastern Sichuan corresponds to the low-level southerly anomalies to the east of Sichuan, which curve into northeasterly anomalies over the basin when they encounter the mountains to the north of the basin. Therefore, it can be concluded that the topography in and around Sichuan plays a crucial role in inducing extreme rainfall both over western and eastern Sichuan. Finally, the enhanced extreme rainfall in western and eastern Sichuan is related to warmer SSTs in the Maritime Continent and cooler SSTs in the equatorial central Pacific, respectively.
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