A review of downscaling methods of satellite-based precipitation estimates

Satellite remote sensing is the main tool for estimating precipitation over areas with sparse rain gauge networks. Accurate gridded precipitation data at high temporal and spatial scales are needed for various studies such as hydrology, climatology, and meteorology. Meanwhile, downscaling of satellite precipitation products is necessary to attain such data because their spatial resolutions are too coarse for use in local region and basin scales or for parameterizing meteorological and hydrological models at a local scale. In recent years, plenty of attempts have been made to improve the resolutions of satellite-based precipitation estimates, and many algorithms have been proposed for this purpose. A review study of existing methods can help improve and develop future precipitation downscaling algorithms. Therefore, in this paper, the existing downscaling methods are reviewed, categorized, and summarized. Also, the performance of these methods in the studied regions is compared, and their advantages and limitations are highlighted. Finally, we concluded by stating the necessary considerations for future studies.