Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging

Water

Zhe Li¹  Yintang Wang²  Yong Huang²  Lingjie Li²  Leizhi Wang²  Qingfang Hu² 

[1] Key Laboratory of Terrestrial Water Cycle and Surface Processes, Institute of Geographical Sciences and Resources, Chinese Academy of Sciences, Beijing 100101, China;State Key Laboratory of Hydrology, Water Resources and Hydraulic Engineering Science, Nanjing Hydraulic Research Institute, Nanjing 210029, China;

关键词: rainfall;    spatial interpolation;    radar;    satellite;    atmospheric reanalysis;    rainfall merging;   

DOI  :  10.3390/w11030579

来源: DOAJ

【 摘 要 】

Rainfall is one of the most basic meteorological and hydrological elements. Quantitative rainfall estimation has always been a common concern in many fields of research and practice, such as meteorology, hydrology, and environment, as well as being one of the most important research hotspots in various fields nowadays. Due to the development of space observation technology and statistics, progress has been made in rainfall quantitative spatial estimation, which has continuously deepened our understanding of the water cycle across different space-time scales. In light of the information sources used in rainfall spatial estimation, this paper summarized the research progress in traditional spatial interpolation, remote sensing retrieval, atmospheric reanalysis rainfall, and multi-source rainfall merging since 2000. However, because of the extremely complex spatiotemporal variability and physical mechanism of rainfall, it is still quite challenging to obtain rainfall spatial distribution with high quality and resolution. Therefore, we present existing problems that require further exploration, including the improvement of interpolation and merging methods, the comprehensive evaluation of remote sensing, and the reanalysis of rainfall data and in-depth application of non-gauge based rainfall data.

【 授权许可】

Unknown