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

被引：0
|
作者：
Xiong L. [1 ]
Liu C. [1 ]
Chen S. [2 ]
Zha X. [1 ]
Ma Q. [3 ]
机构：
[1] State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan
[2] Changjiang Institute of Survey, Planning, Design and Research, Wuhan
[3] Renewable Energy School, North China Electric Power University, Beijing
来源：
| 1600年 / International Research and Training Center on Erosion and Sedimentation and China Water and Power Press卷 / 32期
基金：
中国国家自然科学基金;
关键词：
Bias correction; Evaluation indices; Multi-product fusion; Rain gauge; Remote-sensing precipitation; Spatial downscaling;
D O I：
10.14042/j.cnki.32.1309.2021.04.014
中图分类号：
学科分类号：
摘要：
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. © 2021, Editorial Board of Advances in Water Science. All right reserved.
引用
收藏
页码：627 / 637
页数：10
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