Abstract
This paper uses enhanced vegetation index (EVI) data, normalized vegetation index (NDVI) data, DEM, aspect data, and TRMM3B43 (V7) data, based on a geographically weighted regression model (GWR), and uses a statistical downscaling method to achieve Central China Downscaling of regional TRMM data from 2010 to 2019. The research results show: (1) TRMM data has good applicability in Central China, and the R2of TRMM data and weather station measured data is above 0.8. (2) Improve the ground resolution from 0.25°×0.25° (approximately 27.5km×27.5km) to 1km×1km while ensuring the same accuracy as the original data. (3) Overall, the accuracy of EVI downscaled precipitation data in Central China is better than that of NDVI downscaled precipitation data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
