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A Posteriori Random Forests For Stochastic Downsca by A GB is a document available to read on EtoBox.
This research article introduces a posteriori random forests (AP-RFs) for the stochastic downscaling of precipitation, enhancing traditional random forests by predicting probability distributions rather than deterministic values. The study demonstrates that AP-RFs can generate realistic stochastic precipitation samples on wet days, improving distributional similarity with observed data while maintaining predictive power. This methodology holds significant potential for hydrologists and impact communities re
- Author
- A GB
- Language
- EN