沙尘是中国北方典型的灾害天气。构建长时间尺度东亚地区高分辨率沙尘气溶胶质量浓度再分析数据集,是深化理解中国沙尘天气发生机理和提升多尺度预报水平的数据基础。受到风蚀起沙过程参数化方案、长距离输送误差等限制,当前沙尘模拟结...沙尘是中国北方典型的灾害天气。构建长时间尺度东亚地区高分辨率沙尘气溶胶质量浓度再分析数据集,是深化理解中国沙尘天气发生机理和提升多尺度预报水平的数据基础。受到风蚀起沙过程参数化方案、长距离输送误差等限制,当前沙尘模拟结果存在较大不确定性。鉴于此,本研究在前期开发的沙尘同化系统基础上,集成地面PM_(10)质量浓度、卫星气溶胶光学厚度(aerosol optical depth,AOD)观测非沙尘组分偏差校正技术,以及适用于沙尘气溶胶强度、位置误差协同校正的有效时刻偏移卡尔曼滤波同化算法(valid time shift ensemble Kalman filter,VTS-EnKF),建立了10 a(2014—2023年)东亚地区春季(3—5月)逐3 h的沙尘气溶胶三维质量浓度再分析数据集,分辨率为0.25°×0.25°。在此基础上,分析了所建立的再分析数据集相较于MERRA-2(modern-era retrospective analysis for research and applications version 2)沙尘再分析产品的优势,同时讨论了过去10 a东亚地区春季沙尘天气的月、年际变化趋势。展开更多
Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives ...Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.展开更多
An unprecedented extreme gale and dust event struck East Asia during 10-14 April2025.A record-breaking gale swept across most regions of China.It carried large amounts of dust from northern deserts,resulting in nation...An unprecedented extreme gale and dust event struck East Asia during 10-14 April2025.A record-breaking gale swept across most regions of China.It carried large amounts of dust from northern deserts,resulting in nationwide dust weather.Gales affected more than 3.5 million km^(2),and the windspeeds in North China were the strongest in April since 1940(Fig.1a,b).展开更多
The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.展开更多
Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and dr...Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.展开更多
文摘沙尘是中国北方典型的灾害天气。构建长时间尺度东亚地区高分辨率沙尘气溶胶质量浓度再分析数据集,是深化理解中国沙尘天气发生机理和提升多尺度预报水平的数据基础。受到风蚀起沙过程参数化方案、长距离输送误差等限制,当前沙尘模拟结果存在较大不确定性。鉴于此,本研究在前期开发的沙尘同化系统基础上,集成地面PM_(10)质量浓度、卫星气溶胶光学厚度(aerosol optical depth,AOD)观测非沙尘组分偏差校正技术,以及适用于沙尘气溶胶强度、位置误差协同校正的有效时刻偏移卡尔曼滤波同化算法(valid time shift ensemble Kalman filter,VTS-EnKF),建立了10 a(2014—2023年)东亚地区春季(3—5月)逐3 h的沙尘气溶胶三维质量浓度再分析数据集,分辨率为0.25°×0.25°。在此基础上,分析了所建立的再分析数据集相较于MERRA-2(modern-era retrospective analysis for research and applications version 2)沙尘再分析产品的优势,同时讨论了过去10 a东亚地区春季沙尘天气的月、年际变化趋势。
基金supported by the National Natural Science Foundation of China(Grant No.U2342208)support from NSF/Climate Dynamics Award#2025057。
文摘Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.
基金supported by the National Natural Science Foundation of China(42088101).
文摘An unprecedented extreme gale and dust event struck East Asia during 10-14 April2025.A record-breaking gale swept across most regions of China.It carried large amounts of dust from northern deserts,resulting in nationwide dust weather.Gales affected more than 3.5 million km^(2),and the windspeeds in North China were the strongest in April since 1940(Fig.1a,b).
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
基金funded by the National Natural Science Foundation of China(42571311).
文摘Central Asia is characterized by an arid climate and widespread desert distribution,with its sustainable development severely constrained by dust events.An objective understanding of the spatiotemporal patterns and driving forces of dust weather is highly important in this area.Based on the meteorological observations from 2000 to 2020,we examined the spatiotemporal characteristics of dust weather in the five Central Asian countries(Kazakhstan,Uzbekistan,Kyrgyzstan,Turkmenistan,and Tajikistan)via Theil-Sen trend analysis and Geodetector modeling method,quantitatively revealing the influence of environmental factors,such as temperature,precipitation,and vegetation,on the frequency of dust weather.The results showed that:(1)dust weather in Central Asia was mainly distributed in a large''dust belt''extending from west to east from northern part of the Caspian lowland desert,and concentrated in basins,plains,and other low-altitude areas.Strong dust weather mainly occurred in northern areas of the Aral Sea and southern edge of Central Asia,with a maximum annual frequency of 21.9%;(2)strong dust weather in Central Asia has fluctuated and slightly decreased since 2001.The highest frequency(1.1%)occurred in spring(from March to June);(3)from 2000 to 2020,changes such as spot shifting and shrinking occurred in the four main source areas(north of the Aral Sea,Kyzylkum Desert,Karakum Desert,and Garabogazköl Bay region),where sandstorms occurred in Central Asia,and northern Caspian lowland desert became the most important low-emission dust source in Central Asia;and(4)the combined effect of soil moisture and air temperature has the most significant influence on dust weather in Central Asia.This study provides a theoretical basis for sand prevention and sand control in Central Asia.In the future,Central Asia should focus on the rational utilization of land and water resources,and implement human interventions such as vegetation restoration and optimization of irrigation methods to curb further desertification in this area.
