Global daily 1 km land surface precipitation based on cloud cover-informed downscaling.

ABSTRACT: High-resolution climatic data are essential to many questions and applications in environmental research and ecology. Here we develop and implement a new semi-mechanistic downscaling approach for daily precipitation estimate that incorporates high resolution (30 arcsec, ≈1 km) satellite-derived cloud frequency. The downscaling algorithm incorporates orographic predictors such as wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. We apply the method to the ERA5 precipitation archive and MODIS monthly cloud cover frequency to develop a daily gridded precipitation time series in 1 km resolution for the years 2003 onward. Comparison of the predictions with existing gridded products and station data from the Global Historical Climate Network indicates

SUBMITTER: Karger DN 

PROVIDER: S-EPMC8626457 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature