Preprint
Comparison of data-driven methods for downscaling ensemble weather forecasts
Abstract
This study investigates dynamically different data-driven methods, specifically a statistical downscaling model (SDSM), a time lagged feedforward neural network (TLFN), and an evolutionary polynomial regression (EPR) technique for downscaling numerical weather ensemble forecasts generated by a medium range forecast (MRF) model. Given the coarse resolution (about 200-km grid spacing) of the MRF model, an optimal use of the weather forecasts at …
Authors
Liu X; Coulibaly P; Evora N
Pagination
pp. 189-210
DOI
10.5194/hessd-4-189-2007
Preprint server
EGUsphere