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Error analysis of multi-satellite precipitation estimates with an independent raingauge observation network over a medium-sized humid basin

机译:利用独立雨量计观测网络对中型湿润盆地进行多卫星降水估算的误差分析

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摘要

This study focuses on quantifying the error characteristics of four widely utilized satellite precipitation products (i.e. TMPA 3B42RTV7, TMPA 3B42V7, CMORPH and PERSIANN-CDR) for a five-year period (2005-2009) using an independent raingauge network over the upper-middle Huai River basin in central-eastern China. Assessment results show that CMORPH generally exhibits the best performance with slight underestimation, while 3B42RTV7 has the worst performance with large positive biases. Additionally, 3B42V7 and PERSIANN-CDR tend to have an approximate accuracy. The monthly gauge adjustment applied to 3B42V7 and PERSIANN-CDR significantly reduces their systematic bias and in particular it makes these two research products maintain a stable skill level during winter. As for the heavy rainfall events (>50mm/d) in summer, 3B42V7 and CMORPH exhibit a relatively better degree of agreement to the gauge observations. Overall, our study suggests that the satellite-based precipitation estimates all have their own pros and cons at different spatiotemporal scales. We expect the results reported here will provide a better understanding of current mainstream satellite precipitation products over similar medium-sized humid basins.
机译:这项研究的重点是使用独立的雨量计网络在中上层地区量化五年(2005-2009年)四种广泛使用的卫星降水产品(即TMPA 3B42RTV7,TMPA 3B42V7,CMORPH和PERSIANN-CDR)的误差特征。淮河流域在中国中东部。评估结果表明,CMORPH通常表现出最佳性能,但被低估了一些,而3B42RTV7表现最差,具有较大的正偏差。此外,3B42V7和PERSIANN-CDR往往具有近似的准确性。每月对3B42V7和PERSIANN-CDR进行的量规调整会大大降低其系统偏差,尤其是这使这两个研究产品在冬季保持稳定的技能水平。对于夏季的强降雨事件(> 50mm / d),3B42V7和CMORPH与标准观测值显示出相对较好的一致性。总体而言,我们的研究表明,基于卫星的降水估计在不同时空尺度上各有利弊。我们希望这里报告的结果将更好地了解类似中型湿盆地中当前的主流卫星降水产品。

著录项

  • 来源
    《Hydrological sciences journal》 |2016年第12期|1813-1830|共18页
  • 作者单位

    Nanjing Univ Informat Sci & Technol, Coll Hydrometeorol, 219 Ningliu Rd, Nanjing 210044, Jiangsu, Peoples R China|SOA, State Key Lab Satellite Ocean Environm Dynam, Inst Oceanog 2, Hangzhou 310012, Zhejiang, Peoples R China|Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, 1 Xikang Rd, Nanjing 210098, Jiangsu, Peoples R China;

    Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, 1 Xikang Rd, Nanjing 210098, Jiangsu, Peoples R China;

    Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73072 USA|Natl Weather Ctr, Adv Radar Res Ctr, Norman, OK 73072 USA;

    Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73072 USA|Natl Weather Ctr, Adv Radar Res Ctr, Norman, OK 73072 USA;

    Sichuan Univ, State Key Lab Hydraul & Mt River Engn, 24 South Sect 1,Yihuan Rd, Chengdu 610065, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Satellite precipitation; error characteristics; Huai River basin; statistical evaluation; raingauge observation;

    机译:卫星降水;误差特征;淮河流域;统计评估;雨量计观测;
  • 入库时间 2022-08-18 03:39:34

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