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黄河中上游多源降水数据精度评估 被引量:1

Accuracy Evaluation of Multi-source Precipitation Data in the Middle and Upper Reaches of the Yellow River
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摘要 为研究黄河中上游遥感降水数据的可替代性,以2001~2010年站点实测降水数据为依据,采用相关系数、均方根误差和平均误差三个指标,分别从年、季、月尺度对14种卫星降水数据进行精度评价,并以水系为空间单元对极端降水事件进行评估。结果表明,在年、季、月尺度上,ITPCAS的精度均相对较高,GSMaP、PERSIANN的精度最低。季节上,降水数据均易高估春、夏季暴雨以下降水,低估暴雨以上降水;均易高估秋季大雨以下降水,低估大雨以上降水。对于极端降水,GSMaP、CHIRPS呈严重高估,PERSIANN呈严重低估;区域上,甘宁、内蒙水系各数据集对极端降水的评估与实测降水的一致性较强,其余水系中各数据集对极端降水评估的精度差异较大。 In order to study the substitutability of remote sensing precipitation data in the middle and upper reaches of the Yellow River Basin, based on the measured precipitation data during 2001-2010, the correlation coefficient, root mean square error and average error were used to evaluate the accuracy of 14 kinds of satellite precipitation data from the annual, quarterly and monthly scales respectively, and the extreme precipitation events were evaluated by taking water system as space unit. The results show that on the annual, seasonal and monthly scales, the accuracy of ITPCAS is relatively high, and that of GSMaP and PERSIANN is the lowest. In spring and summer, the precipitation data tend to be overestimated the precipitation below the rainstorm and underestimated the precipitation above the rainstorm;In autumn, they tend to be overestimated the precipitation below the heavy rain(25-50 mm) and underestimated the precipitation above the heavy rain(25-50 mm). For the extreme precipitation events, the GSMaP and CHIRPS are seriously overestimated, and PERSIANN is seriously underestimated. On the whole, the data sets of Ganning and Inner Mongolia river system have a strong consistency with the measured precipitation, and the accuracy of other data sets varies greatly in each basin.
作者 慎璐璐 杨艳芬 白磊 吴晶 SHEN Lu-lu;YANG Yan-fen;BAI Lei;WU Jing(State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau,Institute of Soil and Water Conservation,Northwest A&F University,Yangling 712100,China;College of Ecology and Environment Hainan University,Haikou 570228,China;Lanzhou Central Meteorological Observatory,Lanzhou 730020,China)
出处 《水电能源科学》 北大核心 2022年第2期1-5,共5页 Water Resources and Power
基金 国家重点研发计划(2016YFC0501603)。
关键词 卫星降水数据 精度评估 极端降水 时空分布 黄河中上游 satellite precipitation data accuracy evaluation extreme precipitation spatio-temporal variation the middle and upper reaches of the Yellow River
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