Joint wavelet decomposition of predictors and target variables for drought forecasting

Abstract We propose a leakage-free wavelet-based methodology for drought prediction that enables both competitive forecasting performance and improved interpretability of predictor–target relationships. Unlike standard time-series decomposition approaches, the wavelet transform is applied within moving windows of the past values, preventing the use of future information during model training. The method merges local and large-scale climate predictors across multiple temporal scales and is evalua