Statistical downscaling of daily precipitation and the stationarity assumption
The study region examined here focuses on 16 points across North America. We evaluated the downscaled results in terms of historical and future mean absolute error skill score (MAE SS) to assess if the skills were time-invariant. Our results show that for 9 out 16 points our hybrid CART-SVR downscaling model had positive historical and future MAE SS. We also found that the CART model under predicted the total number of rainy days. Future implementations will test other classification methods (e.g. support vector classification, drizzle threshold) and will expand the predictor set aiming to improve the overall MAE SS.