Cluster-based downscaling of precipitation using Kolmogorov-Arnold Neural Networks and CMIP6 models: Insights from Oman.

Accurate precipitation predictions are crucial for addressing climate change impacts on water resources, especially in arid regions like Oman. Therefore, this study evaluates three machine learning models-Random Forest (RF), Multilayer Perceptron Neural Networks (MLP-ANN), and Kolmogorov-Arnold Neural Networks (KANNs)-to downscale and predict precipitation patterns under climate scenarios SSP1-2.6, SSP2-4.