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多源卫星降水产品在西南地区的精度评估与比较分析
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Abstract:
基于亚洲地区高质量高时空分辨率降水数据集AIMERG，利用5个统计指标评估和比较CMORPH-BLD、PERSIANN-CDR、TRMM-3B42V7、TRMM_RT-3B42V7卫星降水数据在西南地区的降水检测能力。结果表明：各卫星产品均能准确反映降水的月变化特征，但降水量越大，估算的精度越差。相比之下PERSIANN-CDR数据精度最高。春季、夏季和秋季TRMM_RT-3B42V7产品对降水季节变化趋势捕获能力较强，但是对各网格点降水的估算偏差较大，CMORPH-BLD、PERSIANN-CDR和TRMM-3B42V7产品对降水估算的精度正好相反。冬季TRMM_RT-3B42V7产品对降水估算的精度较差，CMORPH-BLD、PERSIANN-CDR和TRMM-3B42V7产品对降水估算的精度较好，其中又以PERSIANN-CDR数据精度最高。各卫星产品均能捕获降水年际变化特征，但明显有高估或者低估。4种卫星产品在贵州大部、云南南部和西藏东部对降水均表现出较好的估算能力，而在重庆地区对降水的估算能力较差。
Based on the Asian precipitation dataset with high quality and spatiotemporal resolution (AIMERG) of ground grid precipitation product, five statistical indicators are used to evaluate and compare the rain-fall monitoring capabilities of Climate Prediction Center Morphing technique satellite-gauge blended datasets (CMORPH-BLD), Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Tropical Rainfall Measuring Mission (TRMM_RT-3B42V7) satellite data sources in Southwest China. The results show that the four satellite products can accurately model the monthly variation characteristics of precipitation, while the greater the precipitation is, the worse the estimation accuracy of satellite products is. By comparison, the data precision of PERSIANN-CDR is the highest. The trend of seasonal precipitation can be well modeled by TRMM_RT-3B42V7 product in spring, summer and autumn, but the estimation deviation of precipitation from gridded data is larger, which is contrary to those of CMORPH-BLD, PERSIANN-CDR and TRMM-3B42V7 products. In winter, the accuracy of precipitation estimation of TRMM_RT-3B42V7 production is worse, while the accuracy of precipitation estimation of CMORPH-BLD, PERSIANN-CDR and TRMM-3B42V7 productions is all better, among which PERSIANN-CDR production performs best. The trend of annual precipitation variation can be simulated well by the four satellite precipitation products, which is either overestimated or underestimated. These products show better capability of estimation precipitation in most parts of Guizhou, southern Yunnan and eastern Tibet and show worse capability of estimation precipitation in Chongqing region.
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