熊立华, 刘成凯, 陈石磊, 查悉妮, 马秋梅. 遥感降水资料后处理研究综述[J]. 水科学进展, 2021, 32(4): 627-637. DOI: 10.14042/j.cnki.32.1309.2021.04.014
引用本文: 熊立华, 刘成凯, 陈石磊, 查悉妮, 马秋梅. 遥感降水资料后处理研究综述[J]. 水科学进展, 2021, 32(4): 627-637. DOI: 10.14042/j.cnki.32.1309.2021.04.014
XIONG Lihua, LIU Chengkai, CHEN Shilei, ZHA Xini, MA Qiumei. Review of post-processing research for remote-sensing precipitation products[J]. Advances in Water Science, 2021, 32(4): 627-637. DOI: 10.14042/j.cnki.32.1309.2021.04.014
Citation: XIONG Lihua, LIU Chengkai, CHEN Shilei, ZHA Xini, MA Qiumei. Review of post-processing research for remote-sensing precipitation products[J]. Advances in Water Science, 2021, 32(4): 627-637. DOI: 10.14042/j.cnki.32.1309.2021.04.014

遥感降水资料后处理研究综述

Review of post-processing research for remote-sensing precipitation products

  • 摘要: 获取高精度高分辨率的降水数据对于流域水文分析、水资源管理及洪涝干旱监测等均具有重要意义。遥感技术虽然能有效再现降水的时空分布,但原始遥感降水资料无法满足水文领域对高精度高分辨率数据的需求,需要开展遥感降水资料的后处理研究。介绍获取降水资料的主要方法,包括雨量站观测、地面天气雷达估测以及气象卫星反演,讨论各方法的主要优势和当前存在的问题,在此基础上综述遥感降水资料的后处理方法研究进展,包括空间降尺度、偏差校正以及产品融合,并归纳后处理降水产品的评价指标,最后指出今后的研究重点:发展和改进降水估计技术;构建更为合理的多源降水数据融合框架;加强降尺度法对比研究,进一步改进和完善降尺度法;开展降水相关的不确定性分析。

     

    Abstract: Obtaining high-precision, high-resolution precipitation data is of great significance for hydrological analysis, water resources management, and flood and drought monitoring. Although remote-sensing precipitation products can effectively reproduce the spatial and temporal distribution of precipitation, few original remote-sensing precipitation products can meet the requirements in either precision or resolution in the hydrological field. It is therefore necessary to carry out post-processing research on existing remote-sensing precipitation products. The main methods used to obtain precipitation data are introduced, including rain-gauge observations, weather radar estimates, and satellite products. The advantages of each method and their problems are discussed. Next, the research advances made in post-processing methods of remote-sensing precipitation products are summarized, including spatial downscaling, bias correction, and multi-product fusion. Then, the indices used for evaluation of post-processing precipitation products are reviewed. Finally, the following research directions that must be pursued more avidly in the future are discussed: development and improvement of precipitation-estimation techniques, construction of a more reasonable framework for multi-source precipitation data fusion, strengthening of the comparative study of downscaling methods and ideas for their improvement, and uncertainty analysis.

     

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