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长三角地区常用遥感降水产品质量评估
引用本文:李强宇,楚岱蔚,朱晓晨.长三角地区常用遥感降水产品质量评估[J].科学技术与工程,2021,21(12):4801-4810.
作者姓名:李强宇  楚岱蔚  朱晓晨
作者单位:南京信息工程大学应用气象学院,南京210044;浙江省杭州市余杭区气象局,杭州311100
基金项目:国家自然科学基金(41805049)和南京信息工程大学人才启动项目(2018r009)
摘    要:长三角地区是中国经济最发达地区之一,选定较好的卫星降水产品是进行科学防灾减灾的重要环节.基于地面气象站降水实测数据,采用7种指标对目前中外常用遥感降水产品热带降水任务卫星(tropical rainfall measurement mission,TRMM)、气候预测中心校正产品(climate prediction center morphing technique,CMORPH)、全球降水计划数据集(global precipi-tation measurement,GPM)以及中国自动站与CMORPH降水产品融合数据集(China merged precipitation analysis,CMPA)在长三角地区的适用性进行评估.结果表明:在年尺度,CMPA产品质量最优,相关系数达到0.95;在季节尺度,冬季GPM最优,夏季TRMM最优;平原地区比山区地区的产品质量要好.融合多降水产品的高精度产品未来将成为科学防灾减灾的重要数据.

关 键 词:卫星降水产品  融合降水资料  全球降水计划数据集(GPM)  气候预测中心校正产品(CMORPH)  适用性评估
收稿时间:2020/7/28 0:00:00
修稿时间:2021/2/7 0:00:00

Study on the Quality Evaluation of Precipitation Products Commonly Used by Remote Sensing in the Yangtze River Delta
Li Qiangyu,Chu Daiwei,Zhu Xiaochen.Study on the Quality Evaluation of Precipitation Products Commonly Used by Remote Sensing in the Yangtze River Delta[J].Science Technology and Engineering,2021,21(12):4801-4810.
Authors:Li Qiangyu  Chu Daiwei  Zhu Xiaochen
Institution:Nanjing University of Information Science & Technology;Yuhang Meteorological Bureau, Hangzhou
Abstract:The Yangtze River Delta region is one of the most economically developed regions in China. Choosing better satellite precipitation products is an important part of scientific disaster prevention and mitigation. In this study, we use seven indicators to evaluate the applicability of remote sensing precipitation products TRMM, CMORPH, GPM, and CMPA in the Yangtze River Delta region based on the precipitation data from the weather stations. The results show that on the annual scale, the CMPA product quality is the best, with a correlation coefficient of 0.95; on the seasonal scale, the GPM in winter is the best, and the TRMM in the summer is the best; the product quality in plain areas is better than mountain areas. High-precision products that incorporate precipitation-rich products will become important data for scientific disaster prevention and mitigation in the future.
Keywords:Satellite precipitation products  fusion precipitation data  GPM  CMORPH  applicability assessment
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