综合评价了全球性降水数据MSWEP(Multi-Source Weighted-Ensemble Precipitation)在祁连山区的适用性,解析了其在不同时空尺度上的误差特征,采用结合地面雨量资料GSOD(Global Surface Summary of the Day)订正后的MSWEP(Corrected MSWEP...综合评价了全球性降水数据MSWEP(Multi-Source Weighted-Ensemble Precipitation)在祁连山区的适用性,解析了其在不同时空尺度上的误差特征,采用结合地面雨量资料GSOD(Global Surface Summary of the Day)订正后的MSWEP(Corrected MSWEP,COMSWEP),重点探讨了祁连山地区降水的垂直分布特性。结果表明:(1)MSWEP在日、月、年等尺度上总体低估了研究区域地表降水,对暴雨及以上日降水事件存在比较严重的漏报,在雨季的精度要明显高于旱季;(2)相对于MSWEP,COMSWEP在各种时间尺度上与地表降水更为吻合,对雨季降水和年降水具有较好估计效果,但在旱季仍存在较明显系统偏差;(3)MSWEP和COMSWEP均表明祁连山区多年平均降水量在空间上呈由东至西递减、北坡略高于南坡的总体格局,而在时程上雨季降水主导了全年降水,但在不同分区和时间尺度上,COMSWEP降水量均明显高于MSWEP;(4)MSWEP和COMSWEP均反映祁连山地区东段最大降水高度带在3000 m左右,超过此高度带多年平均降水量变化甚小,而中段和西段多年平均降水量随海拔呈现先增加后降低的趋势,最大降水高度带分别位于4100 m和4500 m左右。展开更多
全球性降水数据为获取大范围降水空间分布提供了新途径,但其空间分辨率不高一直是制约其应用于流域或区域尺度上的重要因素之一,因此研究全球性降水数据的空间降尺度方法具有重要的理论和实用价值。本文采用从区域到区域的Kriging(Area ...全球性降水数据为获取大范围降水空间分布提供了新途径,但其空间分辨率不高一直是制约其应用于流域或区域尺度上的重要因素之一,因此研究全球性降水数据的空间降尺度方法具有重要的理论和实用价值。本文采用从区域到区域的Kriging(Area to Area Kriging,ATAK)和反距离权重(Inverse Distance Weighted,IDW)两种方法,不考虑地面雨量资料及影响雨量的有关辅助信息,在汉江流域将全球性降水数据MSWEP的空间分辨率由0.1°×0.1°提高至0.02°×0.02°。结果发现ATAK降尺度得到的月雨量场虽然在统计精度上与IDW无明显差异,但提高了对月降水量局部空间变异特征的描述能力,在一定程度上克服了IDW的平滑效应。进一步以ATAK、IDW降尺度处理后的MSWEP数据以及不作空间降尺度处理的原始MSWEP数据为背景场,采用GWR方法分别与雨量站网降水数据融合,发现3种情况下得到的月降水融合数据在空间基本格局上相同,精度统计结果也较为接近,但雨量场的空间连续性及细节特征仍有一定差异。在地表雨量站网密度较高的情况下,背景场差异对MSWEP和站点降水融合结果的影响不能完全消除,甚至在局部可能放大。因此,对于MSWEP等全球性降水数据与站网降水资料的融合而言,选择适当的空间降尺度方法是必要的。本文的结论和认识为全球性降水数据的空间降尺度和雨量场精细化估计提供了重要参考。展开更多
Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes...Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes.This paper evaluated the daily performance of four precipitation products(MSWEP,ERA5,PERSIANN,and TRMM)for seven regions of the Chinese mainland,using observations from 2462 ground stations across the country as a benchmark.We used four statistical and four classification indicators to describe their spatial and temporal accuracy,and capability to detect precipitation events while analyzing their applicability.The results show that according to the precipitation char-acteristics and accuracy of different types of precipitation products over the Chinese mainland,MSWEP was the most suitable product over the Chinese mainland,having the lowest root mean square error and mean absolute error,along with the highest coefficient of determination.It was followed by TRMM and ERA5,whereas PERSIANN lagged behind in terms of performance.In terms of different regions,MSWEP still performed well,especially in North China and East China.The accuracy of the four precipitation products was relatively low in the summer months,and they all overestimated in the northwest region.In other months,MSWEP and TRMM were better than PERSIANN and ERA5.The four precipitation products had good detection performance over the Chinese mainland,with probability of detection above 0.5.However,with the increase of precipitation threshold,the detection capability of the four products decreased,and MSWEP and ERA5 had good detection capability for moderate rain.TRMM’s detection capability for heavy rain and rainstorms was better than that of the other three products,and PERSIANN’s detection capability for moderate rain,heavy rain and rainstorms was relatively poor,with a large deviation.展开更多
Multi-source weighted-ensemble precipitation(MSWEP)is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution.While various studies have acknowledged its abilit...Multi-source weighted-ensemble precipitation(MSWEP)is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution.While various studies have acknowledged its ability to accurately estimate precipitation in terms of temporal dynamics,its performance regarding spatial pattern and extreme rainfall is overlooked.To fill this knowledge gap,the daily precipitation of two versions of MSWEP(MSWEP V2.1&V2.2)are compared with that of three representative satellite-and reanalysis-based products,namely the Tropical Rainfall Measuring Mission(TRMM 3B42 V7),the climate prediction center morphing technique satellite-gauge merged product(CMORPH BLD),and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts(ERA5).The comparison is made according to the dense daily rainfall observations from 539 rain gauges over the Huaihe River Basin in China during 2006–2015.The results show that MSWEP V2.1,MSWEP V2.2 and CMORPH BLD have better performance on temporal accuracy of precipitation estimation,followed by ERA5 and TRMM 3B42V7.MSWEPs yield the most even spatial distribution across the basin since it takes full advantage of the multi datasets.As the weighted-ensemble method is independently carried out on each grid in MSWEPs,the spatial distribution of local precipitation is changed by different source data,which results in that MSWEPs perform worse than CMORPH BLD in terms of the representation of precipitation spatial pattern.In addition,the capability of MSWEPs to describe the spatial structure in the rainy season is lower than that in the dry season.Strong precipitation(≥100 mm/d)events are better represented in TRMM 3B42 V7 products than in MSWEPs.Finally,based on the comparison results,we suggest to improve the merging algorithm of MSWEP by considering the precipitation spatial self-correlation and adjusting the merging weights based on the performance of the source datasets under different precipitation intensities.展开更多
文摘全球性降水数据为获取大范围降水空间分布提供了新途径,但其空间分辨率不高一直是制约其应用于流域或区域尺度上的重要因素之一,因此研究全球性降水数据的空间降尺度方法具有重要的理论和实用价值。本文采用从区域到区域的Kriging(Area to Area Kriging,ATAK)和反距离权重(Inverse Distance Weighted,IDW)两种方法,不考虑地面雨量资料及影响雨量的有关辅助信息,在汉江流域将全球性降水数据MSWEP的空间分辨率由0.1°×0.1°提高至0.02°×0.02°。结果发现ATAK降尺度得到的月雨量场虽然在统计精度上与IDW无明显差异,但提高了对月降水量局部空间变异特征的描述能力,在一定程度上克服了IDW的平滑效应。进一步以ATAK、IDW降尺度处理后的MSWEP数据以及不作空间降尺度处理的原始MSWEP数据为背景场,采用GWR方法分别与雨量站网降水数据融合,发现3种情况下得到的月降水融合数据在空间基本格局上相同,精度统计结果也较为接近,但雨量场的空间连续性及细节特征仍有一定差异。在地表雨量站网密度较高的情况下,背景场差异对MSWEP和站点降水融合结果的影响不能完全消除,甚至在局部可能放大。因此,对于MSWEP等全球性降水数据与站网降水资料的融合而言,选择适当的空间降尺度方法是必要的。本文的结论和认识为全球性降水数据的空间降尺度和雨量场精细化估计提供了重要参考。
基金173 National Basic Research Program of China(2020-JCJQ-ZD-087-01)。
文摘Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes.This paper evaluated the daily performance of four precipitation products(MSWEP,ERA5,PERSIANN,and TRMM)for seven regions of the Chinese mainland,using observations from 2462 ground stations across the country as a benchmark.We used four statistical and four classification indicators to describe their spatial and temporal accuracy,and capability to detect precipitation events while analyzing their applicability.The results show that according to the precipitation char-acteristics and accuracy of different types of precipitation products over the Chinese mainland,MSWEP was the most suitable product over the Chinese mainland,having the lowest root mean square error and mean absolute error,along with the highest coefficient of determination.It was followed by TRMM and ERA5,whereas PERSIANN lagged behind in terms of performance.In terms of different regions,MSWEP still performed well,especially in North China and East China.The accuracy of the four precipitation products was relatively low in the summer months,and they all overestimated in the northwest region.In other months,MSWEP and TRMM were better than PERSIANN and ERA5.The four precipitation products had good detection performance over the Chinese mainland,with probability of detection above 0.5.However,with the increase of precipitation threshold,the detection capability of the four products decreased,and MSWEP and ERA5 had good detection capability for moderate rain.TRMM’s detection capability for heavy rain and rainstorms was better than that of the other three products,and PERSIANN’s detection capability for moderate rain,heavy rain and rainstorms was relatively poor,with a large deviation.
基金National Key R&D Program of China,No.2021YFC3000104National Natural Science Foundation of China,No.52009081,No.51479118Special Funded Project for Basic Scientific Research Operation Expenses of the Central Public Welfare Scientific Research Institutes of China,No.Y519006。
文摘Multi-source weighted-ensemble precipitation(MSWEP)is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution.While various studies have acknowledged its ability to accurately estimate precipitation in terms of temporal dynamics,its performance regarding spatial pattern and extreme rainfall is overlooked.To fill this knowledge gap,the daily precipitation of two versions of MSWEP(MSWEP V2.1&V2.2)are compared with that of three representative satellite-and reanalysis-based products,namely the Tropical Rainfall Measuring Mission(TRMM 3B42 V7),the climate prediction center morphing technique satellite-gauge merged product(CMORPH BLD),and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts(ERA5).The comparison is made according to the dense daily rainfall observations from 539 rain gauges over the Huaihe River Basin in China during 2006–2015.The results show that MSWEP V2.1,MSWEP V2.2 and CMORPH BLD have better performance on temporal accuracy of precipitation estimation,followed by ERA5 and TRMM 3B42V7.MSWEPs yield the most even spatial distribution across the basin since it takes full advantage of the multi datasets.As the weighted-ensemble method is independently carried out on each grid in MSWEPs,the spatial distribution of local precipitation is changed by different source data,which results in that MSWEPs perform worse than CMORPH BLD in terms of the representation of precipitation spatial pattern.In addition,the capability of MSWEPs to describe the spatial structure in the rainy season is lower than that in the dry season.Strong precipitation(≥100 mm/d)events are better represented in TRMM 3B42 V7 products than in MSWEPs.Finally,based on the comparison results,we suggest to improve the merging algorithm of MSWEP by considering the precipitation spatial self-correlation and adjusting the merging weights based on the performance of the source datasets under different precipitation intensities.
