Being largely dependent on agriculture, the overall development and water resource management of Bangladesh are greatly influenced by the accurate estimation of precipitation. Different satellite derived precipitation...Being largely dependent on agriculture, the overall development and water resource management of Bangladesh are greatly influenced by the accurate estimation of precipitation. Different satellite derived precipitation products, covering a large area, are very useful for rainfall estimation. In this study, three different satellite precipitation datasets namely Climate Prediction Center MORPHING (CMORPH), the global Satellite Mapping of Precipitation (GSMaP), and the Integrated Multi-satellitE Retrievals for GPM (IMERG) daily data are spatially analyzed and compared with the observed rainfall data from 20<sup>th</sup> May 2020 to 21<sup>st</sup> May 2020. It is observed that the satellite products matched well with the observed data set but the amount varied. Also, the spatial distribution of CMORPH and GSMaP with the observed precipitation is represented for 02 May 2019.展开更多
降水数据产品的兴起为水文气象领域研究提供了新思路,为缺资料地区水文预报、水资源管控提供有力数据支撑。作为站点数据的重要补充,其准确性对径流模拟、水文测报等至关重要。郑州市近些年暴雨事件频发,地面雨量站数量较少,不足以支撑...降水数据产品的兴起为水文气象领域研究提供了新思路,为缺资料地区水文预报、水资源管控提供有力数据支撑。作为站点数据的重要补充,其准确性对径流模拟、水文测报等至关重要。郑州市近些年暴雨事件频发,地面雨量站数量较少,不足以支撑水文气象工作者制定决策,通过定量指标与分类指标评估中国区域地面气象要素驱动数据集(CMFD)、Integrated Multi-satellitE Retrievals for GPM final run(GPM IMERG)、欧洲中期天气预报中心第5代再分析数据(ERA5)及Global Satellite Mapping of Precipitation(GSMaP)4套降水数据产品,筛选出适用于郑州市的降水数据,并采用Slope分析法及MK检验法揭示郑州市降水时空演变规律。结果表明:4种卫星降水产品在郑州市均取得较好适用性,其中CMFD在总体上表现最优;4套降水数据均表现出高估小雨,低估中雨和大雨的现象;在空间上,4套降水数据在郑州市西南区域总体表现优于东北区域;郑州市降水在时间上呈现不显著下降趋势,下降率约为0.2 mm/a,在空间上,呈现出自西南向东北递减的趋势。展开更多
文摘Being largely dependent on agriculture, the overall development and water resource management of Bangladesh are greatly influenced by the accurate estimation of precipitation. Different satellite derived precipitation products, covering a large area, are very useful for rainfall estimation. In this study, three different satellite precipitation datasets namely Climate Prediction Center MORPHING (CMORPH), the global Satellite Mapping of Precipitation (GSMaP), and the Integrated Multi-satellitE Retrievals for GPM (IMERG) daily data are spatially analyzed and compared with the observed rainfall data from 20<sup>th</sup> May 2020 to 21<sup>st</sup> May 2020. It is observed that the satellite products matched well with the observed data set but the amount varied. Also, the spatial distribution of CMORPH and GSMaP with the observed precipitation is represented for 02 May 2019.
文摘降水数据产品的兴起为水文气象领域研究提供了新思路,为缺资料地区水文预报、水资源管控提供有力数据支撑。作为站点数据的重要补充,其准确性对径流模拟、水文测报等至关重要。郑州市近些年暴雨事件频发,地面雨量站数量较少,不足以支撑水文气象工作者制定决策,通过定量指标与分类指标评估中国区域地面气象要素驱动数据集(CMFD)、Integrated Multi-satellitE Retrievals for GPM final run(GPM IMERG)、欧洲中期天气预报中心第5代再分析数据(ERA5)及Global Satellite Mapping of Precipitation(GSMaP)4套降水数据产品,筛选出适用于郑州市的降水数据,并采用Slope分析法及MK检验法揭示郑州市降水时空演变规律。结果表明:4种卫星降水产品在郑州市均取得较好适用性,其中CMFD在总体上表现最优;4套降水数据均表现出高估小雨,低估中雨和大雨的现象;在空间上,4套降水数据在郑州市西南区域总体表现优于东北区域;郑州市降水在时间上呈现不显著下降趋势,下降率约为0.2 mm/a,在空间上,呈现出自西南向东北递减的趋势。
