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
Sand and dust storms(SDSs)are natural disasters that frequently occur during spring in arid and semi-arid areas,causing serious impacts on human health,air quality,transportation,and agricultural production.Accurately...Sand and dust storms(SDSs)are natural disasters that frequently occur during spring in arid and semi-arid areas,causing serious impacts on human health,air quality,transportation,and agricultural production.Accurately simulating the occurrence and evolution of SDSs is of great significance for identifying dust sources and formulating effective disaster prevention measures.In this study,numerical simulations were conducted to reveal the dynamic spatiotemporal evolution and transport of dust load across East Asia.Using the Weather Research and Forecasting Model coupled with Chemistry(WRF-Chem)and European Centre for Medium-Range Weather Forecasts Reanalysis v5(ERA5)data,the most severe SDS events in the spring of 2023 in East Asia were numerically simulated.The simulated results were compared and validated using meteorological observations and multisource remote sensing data.The results showed that the simulated dust load in the peak regions showed close agreement with ground-based observations during the events.The primary dust sources in spring 2023 were identified as the western desert of Mongolia,the Gobi Desert,and the Taklimakan Desert in Xinjiang Uygur Autonomous Region of China.Peak dust load and maximum wind speed occurred almost simultaneously,indicating that high wind speed was the primary driver of sand and dust mobilization during individual SDS events.Increased surface vegetation covers partially mitigated wind-driven dust emissions.In April,strong winds over the Gobi Desert on the Mongolian Plateau predominantly drove cross-border SDSs along northwestern and northward transport pathways.Dust originating from Mongolia exerts a substantial influence on particulate dust load in the central and eastern parts of Inner Mongolia Autonomous Region of China.In contrast,their impact on the northwestern regions of China remains relatively limited.These findings contribute to understanding the source areas of SDS events in East Asia by simulating the dynamic evolution of SDSs and elucidating the relationships between SDS events and local geographical and environmental factors.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
聚焦塔克拉玛干沙漠人工绿地(塔中)与自然沙地(肖塘)的沙尘传输差异,通过BSNE(big spring number eight)梯度集沙仪采集2024年4月1日—7月10日沙尘样品,系统分析了两地沙尘水平通量及粒度分布特征。研究发现:1)沙尘水平通量空间异质性显...聚焦塔克拉玛干沙漠人工绿地(塔中)与自然沙地(肖塘)的沙尘传输差异,通过BSNE(big spring number eight)梯度集沙仪采集2024年4月1日—7月10日沙尘样品,系统分析了两地沙尘水平通量及粒度分布特征。研究发现:1)沙尘水平通量空间异质性显著,肖塘的沙尘水平通量(65.3 kg·m^(-2)·h^(-1))约为塔中的(29.7 kg·m^(-2)·h^(-1))2.2倍,表明自然沙地更易产生沙尘输送。垂直分布规律呈现明显差异:塔中通量随高度呈“降-增-降”非线性波动,在8和63 m处存在转折点,打破了传统幂函数分布规律;而肖塘通量随高度递减,符合幂函数分布。2)粒度组成以极细沙(48.8%)和粉沙(40.6%)为主,合计占比达89.4%。随高度增加,两地均呈现粉沙比例递增、平均粒径细化的趋势,但塔中整体粒径较粗,分选性更优,峰态分布更集中。3)重力作用导致两地的下层(<10 m)局地物质富集。下垫面和沙尘来源不同是造成沙尘水平通量和粒度分布存在差异的主要因素,风速、风向及植被状况是导致沙尘水平通量随时间变化的重要原因,且随风速的增大而增大。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 Science&Technology Fundamental Resources Investigation Program(2023FY100700)the Key Project of Innovation LREIS(KPI006)+1 种基金the Key R&D and Achievement Transformation Program of Inner Mongolia Autonomous Region(2023KJHZ0027)the Construction Project of China Knowledge Centre for Engineering Sciences and Technology(CKCEST-2023-1-5).
文摘Sand and dust storms(SDSs)are natural disasters that frequently occur during spring in arid and semi-arid areas,causing serious impacts on human health,air quality,transportation,and agricultural production.Accurately simulating the occurrence and evolution of SDSs is of great significance for identifying dust sources and formulating effective disaster prevention measures.In this study,numerical simulations were conducted to reveal the dynamic spatiotemporal evolution and transport of dust load across East Asia.Using the Weather Research and Forecasting Model coupled with Chemistry(WRF-Chem)and European Centre for Medium-Range Weather Forecasts Reanalysis v5(ERA5)data,the most severe SDS events in the spring of 2023 in East Asia were numerically simulated.The simulated results were compared and validated using meteorological observations and multisource remote sensing data.The results showed that the simulated dust load in the peak regions showed close agreement with ground-based observations during the events.The primary dust sources in spring 2023 were identified as the western desert of Mongolia,the Gobi Desert,and the Taklimakan Desert in Xinjiang Uygur Autonomous Region of China.Peak dust load and maximum wind speed occurred almost simultaneously,indicating that high wind speed was the primary driver of sand and dust mobilization during individual SDS events.Increased surface vegetation covers partially mitigated wind-driven dust emissions.In April,strong winds over the Gobi Desert on the Mongolian Plateau predominantly drove cross-border SDSs along northwestern and northward transport pathways.Dust originating from Mongolia exerts a substantial influence on particulate dust load in the central and eastern parts of Inner Mongolia Autonomous Region of China.In contrast,their impact on the northwestern regions of China remains relatively limited.These findings contribute to understanding the source areas of SDS events in East Asia by simulating the dynamic evolution of SDSs and elucidating the relationships between SDS events and local geographical and environmental factors.
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.
文摘聚焦塔克拉玛干沙漠人工绿地(塔中)与自然沙地(肖塘)的沙尘传输差异,通过BSNE(big spring number eight)梯度集沙仪采集2024年4月1日—7月10日沙尘样品,系统分析了两地沙尘水平通量及粒度分布特征。研究发现:1)沙尘水平通量空间异质性显著,肖塘的沙尘水平通量(65.3 kg·m^(-2)·h^(-1))约为塔中的(29.7 kg·m^(-2)·h^(-1))2.2倍,表明自然沙地更易产生沙尘输送。垂直分布规律呈现明显差异:塔中通量随高度呈“降-增-降”非线性波动,在8和63 m处存在转折点,打破了传统幂函数分布规律;而肖塘通量随高度递减,符合幂函数分布。2)粒度组成以极细沙(48.8%)和粉沙(40.6%)为主,合计占比达89.4%。随高度增加,两地均呈现粉沙比例递增、平均粒径细化的趋势,但塔中整体粒径较粗,分选性更优,峰态分布更集中。3)重力作用导致两地的下层(<10 m)局地物质富集。下垫面和沙尘来源不同是造成沙尘水平通量和粒度分布存在差异的主要因素,风速、风向及植被状况是导致沙尘水平通量随时间变化的重要原因,且随风速的增大而增大。
