A Nonparametric Statistical Technique for Spatial Downscaling of Precipitation Over High Mountain Asia

• Published in: Water Resources Research
• Main Authors: Mei, Yiwen, Maggioni, Viviana, Houser, Paul, Xue, Yuan, Rouf, Tasnuva
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: NASA EOSDIS Land Processes DAAC 2020
• Subjects: High Mountain Asia; predictor selection; topographic correction; random forest; precipitation downscaling; Natural Resources and Environment; Science; Merra; The Cryosphere
• Online Access: https://hdl.handle.net/2027.42/163571; https://doi.org/10.1029/2020WR027472

The accurate representation of the local‐scale variability of precipitation plays an important role in understanding the hydrological cycle and land‐atmosphere interactions in the High Mountain Asia region. Therefore, the development of hyper‐resolution precipitation data is of urgent need. In this...