Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 ...Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.展开更多
在利用MODIS卫星的云产品资料对CFSR(Climate Forecast System Reanalysis)再分析资料云产品质量进行检验评估的基础上,采用CFSR资料对1979—2009年全球总云量及低、中、高云量的平均分布及其随纬度的变化进行了分析;用经验模态分解(EMD...在利用MODIS卫星的云产品资料对CFSR(Climate Forecast System Reanalysis)再分析资料云产品质量进行检验评估的基础上,采用CFSR资料对1979—2009年全球总云量及低、中、高云量的平均分布及其随纬度的变化进行了分析;用经验模态分解(EMD)方法分析了近30年全球云量的变化趋势,结果表明:(1)全球近30年平均总云量约为59%,全球总云量及低云量、中云量都有明显的纬向分布特征,全球总云量有3个峰值带和3个低值带。(2)低云量的海陆分布差异较明显,陆地上的低云量明显低于海洋上的,除了两个极圈附近,南半球各纬度的低云量都比北半球相应纬度上的都要多;高云量的高值、低值中心均集中在赤道附近到南、北半球30°之间的中低纬度,并且低值中心主要分布在大洋的东部。(3)总云量的总变化趋势为增长,具体表现为随时间呈现先略减少后大幅增加趋势,其突变点大致在1993年,在1993年之后,总云量显著增多。低云量和高云量均呈现增长趋势,中云量则相反,呈减少趋势。低云量增幅最明显,接近2%,中、高云量则增减幅度较小。展开更多
Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric ...Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric water demand,VPD has implications for global water resources,and its significance extends to the structure and functioning of ecosystems.However,the influence of VPD on vegetation growth under climate change remains unclear in China.This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit(CRU)Time-Series version 4.06(TS4.06)and European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis 5(ERA-5).Vegetation growth status was characterized using three vegetation indices,namely gross primary productivity(GPP),leaf area index(LAI),and near-infrared reflectance of vegetation(NIRv).The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test.Furthermore,the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model.The results indicated an overall negative correlation between VPD and vegetation indices.Three VPD intervals for the correlations between VPD and vegetation indices were identified:a significant positive correlation at VPD below 4.820 hPa,a significant negative correlation at VPD within 4.820–9.000 hPa,and a notable weakening of negative correlation at VPD above 9.000 hPa.VPD exhibited a pronounced negative impact on vegetation growth,surpassing those of temperature,precipitation,and solar radiation in absolute magnitude.CO_(2) contributed most positively to vegetation growth,with VPD offsetting approximately 30.00%of the positive effect of CO_(2).As the rise of VPD decelerated,its relative contribution to vegetation growth diminished.Additionally,the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China.This research provides a theoretical foundation for addressing climate change in China,especially regarding the challenges posed by increasing VPD.展开更多
This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast (below normal, normal, above normal) which was classified based o...This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast (below normal, normal, above normal) which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years (1981-2010). In this study, we used three kinds of monthly data: the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research (NCEP/NCAR) reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.展开更多
基于高分辨率CFSR(climate forecast system reanalysis)风场资料、气候态海洋混合层厚度资料和卫星高度计海面高度异常资料,本文估计了大气风场向全球海洋混合层的近惯性能通量和近惯性能量输入功率,并探究了混合层厚度、风场时间分辨...基于高分辨率CFSR(climate forecast system reanalysis)风场资料、气候态海洋混合层厚度资料和卫星高度计海面高度异常资料,本文估计了大气风场向全球海洋混合层的近惯性能通量和近惯性能量输入功率,并探究了混合层厚度、风场时间分辨率、经验衰减系数和中尺度涡旋涡度对近惯性能通量和能量输入功率的影响。浮标实测风场和流速表明,本文所用的风场和阻尼平板模型可用于估计风场向全球海洋的近惯性能通量。本文计算得到的大气向全球海洋输入近惯性能量的功率为0.56TW(1TW=1012W),其中北半球贡献0.22TW,南半球贡献0.34TW。在时间上,风场的近惯性能通量呈现各个半球冬季最强、夏季最弱的特征,这和西风带风场的季节变化有关。在空间上,近惯性能通量的高值海域为南、北半球西风带海洋,尤其是南大洋。混合层厚度和风场空间不均匀性使得西风带近惯性能通量呈现纬向变化,即海盆西部强于海盆东部。风场时间分辨率对近惯性能通量的估计至关重要,低时间分辨率风场对近惯性能通量的低估达到13%—30%。阻尼平板模型中的经验衰减系数对近惯性能通量估计的影响不超过5%。中尺度涡旋涡度仅改变近惯性能通量的空间分布,而对全球近惯性能量输入功率的影响可以忽略。展开更多
再分析风场资料已广泛应用于我国舟山群岛海域可再生能源评估、海洋灾害预防决策以及港口运维和船舶运输等涉海发展领域,然而不同业务机构所提供的再分析数据在舟山近海的性能表现不一,严重阻碍了此类数据的有效应用。基于2018年全年单...再分析风场资料已广泛应用于我国舟山群岛海域可再生能源评估、海洋灾害预防决策以及港口运维和船舶运输等涉海发展领域,然而不同业务机构所提供的再分析数据在舟山近海的性能表现不一,严重阻碍了此类数据的有效应用。基于2018年全年单点浮标观测资料,综合评价了舟山群岛近海面(10 m)风场的长期变化趋势,并利用误差分析和风玫瑰图等统计工具对6种主流海表风场再分析资料,包括:ECMWF第五代全球大气再分析数据(the 5th generation ECMWF atmospheric reanalysis,ERA5)、NECP第二版全球高分辨率再分析数据(climate forecast system version 2,CFSv2)、美国宇航局物理海洋学分布存档中心的多卫星融合资料(cross-calibrated multi-platform,CCMP)、日本55年再分析数据(Japanese 55-year reanalysis,JRA-55)、第二版现代研究与应用回顾性分析数据(modern-era retrospective analysis for research and applications version 2,MERRA-2)和ECMWF哥白尼大气监测服务再分析数据(the Copernicus Atmosphere Monitoring Service,CAMS)在时间变化特征上进行了对比与评估。研究表明:在综合性能方面,ERA5对风场的再现能力最优,其次为JRA-55;在要素可信度方面,ERA5对风速的再现情况相对较优,而CFSv2的风向再现情况较好;风场产品在不同季节的模拟能力有所差异;不同风场产品在不同风速区间的重构能力也有所不同;在全年风向分布方面,各再分析资料都存在显著的东向偏差。研究结果为不同应用场景下风场资料的选取提供评估依据,并为进一步开发适用于舟山群岛近海的高精度长周期风场数据产品奠定基础。展开更多
Hydro-climatological study is difficult in most of the developing countries due to the paucity of monitoring stations. Gridded climatological data provides an opportunity to extrapolate climate to areas without monito...Hydro-climatological study is difficult in most of the developing countries due to the paucity of monitoring stations. Gridded climatological data provides an opportunity to extrapolate climate to areas without monitoring stations based on their ability to replicate the Spatio-temporal distribution and variability of observed datasets. Simple correlation and error analyses are not enough to predict the variability and distribution of precipitation and temperature. In this study, the coefficient of correlation (R2), Root mean square error (RMSE), mean bias error (MBE) and mean wet and dry spell lengths were used to evaluate the performance of three widely used daily gridded precipitation, maximum and minimum temperature datasets from the Climatic Research Unit (CRU), Princeton University Global Meteorological Forcing (PGF) and Climate Forecast System Reanalysis (CFSR) datasets available over the Niger Delta part of Nigeria. The Standardised Precipitation Index was used to assess the confidence of using gridded precipitation products on water resource management. Results of correlation, error, and spell length analysis revealed that the CRU and PGF datasets performed much better than the CFSR datasets. SPI values also indicate a good association between station and CRU precipitation products. The CFSR datasets in comparison with the other data products in many years overestimated and underestimated the SPI. This indicates weak accuracy in predictability, hence not reliable for water resource management in the study area. However, CRU data products were found to perform much better in most of the statistical assessments conducted. This makes the methods used in this study to be useful for the assessment of various gridded datasets in various hydrological and climatic applications.展开更多
Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relie...Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.展开更多
基金the National Natural Science Foundation of China(42176243)。
文摘Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.
文摘在利用MODIS卫星的云产品资料对CFSR(Climate Forecast System Reanalysis)再分析资料云产品质量进行检验评估的基础上,采用CFSR资料对1979—2009年全球总云量及低、中、高云量的平均分布及其随纬度的变化进行了分析;用经验模态分解(EMD)方法分析了近30年全球云量的变化趋势,结果表明:(1)全球近30年平均总云量约为59%,全球总云量及低云量、中云量都有明显的纬向分布特征,全球总云量有3个峰值带和3个低值带。(2)低云量的海陆分布差异较明显,陆地上的低云量明显低于海洋上的,除了两个极圈附近,南半球各纬度的低云量都比北半球相应纬度上的都要多;高云量的高值、低值中心均集中在赤道附近到南、北半球30°之间的中低纬度,并且低值中心主要分布在大洋的东部。(3)总云量的总变化趋势为增长,具体表现为随时间呈现先略减少后大幅增加趋势,其突变点大致在1993年,在1993年之后,总云量显著增多。低云量和高云量均呈现增长趋势,中云量则相反,呈减少趋势。低云量增幅最明显,接近2%,中、高云量则增减幅度较小。
基金This research was supported by the National Natural Science Foundation of China(42161058).
文摘Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric water demand,VPD has implications for global water resources,and its significance extends to the structure and functioning of ecosystems.However,the influence of VPD on vegetation growth under climate change remains unclear in China.This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit(CRU)Time-Series version 4.06(TS4.06)and European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis 5(ERA-5).Vegetation growth status was characterized using three vegetation indices,namely gross primary productivity(GPP),leaf area index(LAI),and near-infrared reflectance of vegetation(NIRv).The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test.Furthermore,the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model.The results indicated an overall negative correlation between VPD and vegetation indices.Three VPD intervals for the correlations between VPD and vegetation indices were identified:a significant positive correlation at VPD below 4.820 hPa,a significant negative correlation at VPD within 4.820–9.000 hPa,and a notable weakening of negative correlation at VPD above 9.000 hPa.VPD exhibited a pronounced negative impact on vegetation growth,surpassing those of temperature,precipitation,and solar radiation in absolute magnitude.CO_(2) contributed most positively to vegetation growth,with VPD offsetting approximately 30.00%of the positive effect of CO_(2).As the rise of VPD decelerated,its relative contribution to vegetation growth diminished.Additionally,the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China.This research provides a theoretical foundation for addressing climate change in China,especially regarding the challenges posed by increasing VPD.
基金supported by the project "Development and Application of the Techniques on Asian Dust Monitoring and Prediction" of National Institute of Meteorological Research/Korea Meteorological Administration in 2011
文摘This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast (below normal, normal, above normal) which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years (1981-2010). In this study, we used three kinds of monthly data: the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research (NCEP/NCAR) reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.
文摘基于高分辨率CFSR(climate forecast system reanalysis)风场资料、气候态海洋混合层厚度资料和卫星高度计海面高度异常资料,本文估计了大气风场向全球海洋混合层的近惯性能通量和近惯性能量输入功率,并探究了混合层厚度、风场时间分辨率、经验衰减系数和中尺度涡旋涡度对近惯性能通量和能量输入功率的影响。浮标实测风场和流速表明,本文所用的风场和阻尼平板模型可用于估计风场向全球海洋的近惯性能通量。本文计算得到的大气向全球海洋输入近惯性能量的功率为0.56TW(1TW=1012W),其中北半球贡献0.22TW,南半球贡献0.34TW。在时间上,风场的近惯性能通量呈现各个半球冬季最强、夏季最弱的特征,这和西风带风场的季节变化有关。在空间上,近惯性能通量的高值海域为南、北半球西风带海洋,尤其是南大洋。混合层厚度和风场空间不均匀性使得西风带近惯性能通量呈现纬向变化,即海盆西部强于海盆东部。风场时间分辨率对近惯性能通量的估计至关重要,低时间分辨率风场对近惯性能通量的低估达到13%—30%。阻尼平板模型中的经验衰减系数对近惯性能通量估计的影响不超过5%。中尺度涡旋涡度仅改变近惯性能通量的空间分布,而对全球近惯性能量输入功率的影响可以忽略。
文摘再分析风场资料已广泛应用于我国舟山群岛海域可再生能源评估、海洋灾害预防决策以及港口运维和船舶运输等涉海发展领域,然而不同业务机构所提供的再分析数据在舟山近海的性能表现不一,严重阻碍了此类数据的有效应用。基于2018年全年单点浮标观测资料,综合评价了舟山群岛近海面(10 m)风场的长期变化趋势,并利用误差分析和风玫瑰图等统计工具对6种主流海表风场再分析资料,包括:ECMWF第五代全球大气再分析数据(the 5th generation ECMWF atmospheric reanalysis,ERA5)、NECP第二版全球高分辨率再分析数据(climate forecast system version 2,CFSv2)、美国宇航局物理海洋学分布存档中心的多卫星融合资料(cross-calibrated multi-platform,CCMP)、日本55年再分析数据(Japanese 55-year reanalysis,JRA-55)、第二版现代研究与应用回顾性分析数据(modern-era retrospective analysis for research and applications version 2,MERRA-2)和ECMWF哥白尼大气监测服务再分析数据(the Copernicus Atmosphere Monitoring Service,CAMS)在时间变化特征上进行了对比与评估。研究表明:在综合性能方面,ERA5对风场的再现能力最优,其次为JRA-55;在要素可信度方面,ERA5对风速的再现情况相对较优,而CFSv2的风向再现情况较好;风场产品在不同季节的模拟能力有所差异;不同风场产品在不同风速区间的重构能力也有所不同;在全年风向分布方面,各再分析资料都存在显著的东向偏差。研究结果为不同应用场景下风场资料的选取提供评估依据,并为进一步开发适用于舟山群岛近海的高精度长周期风场数据产品奠定基础。
文摘Hydro-climatological study is difficult in most of the developing countries due to the paucity of monitoring stations. Gridded climatological data provides an opportunity to extrapolate climate to areas without monitoring stations based on their ability to replicate the Spatio-temporal distribution and variability of observed datasets. Simple correlation and error analyses are not enough to predict the variability and distribution of precipitation and temperature. In this study, the coefficient of correlation (R2), Root mean square error (RMSE), mean bias error (MBE) and mean wet and dry spell lengths were used to evaluate the performance of three widely used daily gridded precipitation, maximum and minimum temperature datasets from the Climatic Research Unit (CRU), Princeton University Global Meteorological Forcing (PGF) and Climate Forecast System Reanalysis (CFSR) datasets available over the Niger Delta part of Nigeria. The Standardised Precipitation Index was used to assess the confidence of using gridded precipitation products on water resource management. Results of correlation, error, and spell length analysis revealed that the CRU and PGF datasets performed much better than the CFSR datasets. SPI values also indicate a good association between station and CRU precipitation products. The CFSR datasets in comparison with the other data products in many years overestimated and underestimated the SPI. This indicates weak accuracy in predictability, hence not reliable for water resource management in the study area. However, CRU data products were found to perform much better in most of the statistical assessments conducted. This makes the methods used in this study to be useful for the assessment of various gridded datasets in various hydrological and climatic applications.
基金supported by the National Key Research and Development Program of China(2023YFC3206300)the National Natural Science Foundation of China(42477529,42371145,42261026)+2 种基金the China-Pakistan Joint Program of the Chinese Academy of Sciences(046GJHZ2023069MI)the Gansu Provincial Science and Technology Program(22ZD6FA005)the National Cryosphere Desert Data Center(E01Z790201).
文摘Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.