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卫星反演降水在华北极端降水监测中的适用性评估

Evaluation of the Applicability of Satellite-Derived Precipitation in Monitoring Extreme Precipitation in North China

  • 摘要: 基于2000-2023年中国气象局国家基本站降水量日值资料,从极端降水指标统计、极端强降水个例分析等角度,对三种常用卫星反演降水日值产品在华北地区夏季极端降水监测分析中的适用性特征进行了评估,结果表明:1)GSMAP_GNRT6倾向低估降水,尤其在山前区域低估明显,IMERG两种产品则倾向高估降水,尤其在山东半岛高估明显,且以IMERG_V6L高估更明显;2)降水量指数、降水强度指数普遍在高原平原过渡区相关性高于其他区域,强降水频次指数降水较多区域相关性出高于降水较少区域,GSMAP_GNRT6上述指数普遍出现低估,IMERG则对降水量指数出现高估、降水频次和降水强度指数出现低估;3)卫星反演降水能捕捉到极端降水日,但绝对强度普遍显著偏弱,利用百分位和TOP值等相对阈值,其能反映降水极端性的空间分布,但范围偏大,尤以GSMAP_GNRT6偏大最明显,IMERG_V6L表现最好,但较IMERG_V6E优势不明显。总体来看,IMERG和GSMAP在华北夏季极端降水监测分析具备一定应用前景。

     

    Abstract: Strengthening the monitoring and analysis of extreme precipitation is crucial for early warning of disaster weather. Based on daily precipitation data from the national basic stations of China Meteorological Administration from 2000 to 2023, the applicability of three near-real-time daily products of GPM for monitoring extreme precipitation in North China during summer is analyzed from the perspectives of extreme precipitation indices and extreme heavy precipitation events. The results indicate that: 1) IMERG products tend to overestimate precipitation, particularly in the Shandong Peninsula, with IMERG_V6L showing a more pronounced overestimation, in contrast, GSMAP_GNRT6 tends to underestimate precipitation, especially in the foothill regions.2)Precipitation amount and intensity indices generally exhibit higher correlations in the transitional regions between mountains and plains compared to other areas, while precipitation duration and heavy precipitation frequency indices show relatively lower correlations in these regions, and in regions with more precipitation, the correlations are higher than in regions with less precipitation.3) satellite-derived precipitation can capture extreme precipitation days, with IMERG_V6L performing the best, however, the absolute intensity of precipitation is generally significantly underestimated. Using relative thresholds such as percentiles and TOP values can reflect the spatial distribution of extreme precipitation, but there is an issue of overestimation in the spatial extent, with GSMAP_GNRT6 showing the most pronounced overestimation.Overall, IMERG and GSMAP have potential for application in monitoring and analyzing extreme precipitation in North China during summer, but different products should be distinguished and applied according to different regions and application scenarios.。

     

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