TITLE:
Spatial Downscaling of Remote Sensing Precipitation Data in the Beijing-Tianjin-Hebei Region
AUTHORS:
Nuan Wang, Jie Yu, Lin Zhu, Yanbing Wang, Zhengyang He
KEYWORDS:
TRMM, GPM, Spatial Downscaling, Geographically Weighted Regression
JOURNAL NAME:
Journal of Computer and Communications,
Vol.9 No.6,
June
30,
2021
ABSTRACT:
Precipitation is an important part of the global hydrological cycle. The large- scale, high-precision continuous precipitation data obtained by satellite remote sensing detection technology has become an important source of spatial precipitation data. However, because the spatial resolution of remote sensing precipitation data is still low, it is difficult to meet the needs of hydrological research, which restricts their application in drought and flood analysis, hydrological simulation, etc. In response to this problem, this paper takes the Beijing-Tianjin-Hebei region as the research area, downscaling the TRMM data and the GPM data space of the continuation plan, and increasing the spatial resolution of the data to 1 km. Compared with the original data, spatial downscaling data not only greatly improves the spatial resolution, but also increases the accuracy of the data, which has better applicability.