Department of Engineering, University of Cambridge, Cambridge, UK
Publisher's note: the paper was adjusted on 23 April 2025. The adjustments included the typo "chloropeth", the incorrect formatting of the matrix K, the text of the caption of table C2, as well as incorrect years given in the captions of tables 4, C1, and C2.
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a...
