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This study evaluates the cross-region and cross-event generalization of the Wavelet Diffusion Model for precipitation downscaling using U.S. regional data, showing that models trained on limited regions can perform competitively in unseen areas.
Introduces Q-srdrn, a multi-quantile super-resolution network using pinball loss to improve extreme precipitation downscaling, achieving dramatic detection rate gains for heavy rainfall events while maintaining overall accuracy.