Dynamical-statistical downscaling of seasonal hindcasts of temperature and precipitation over South America

Downscaling dinâmico-estatístico de previsões sazonais de temperatura e precipitação para a América do Sul

Abstract

This study aimed to evaluate the performance of the Eta Regional Climate Model in reproducing the seasonal climate over South America for the rainy season from November until April, with emphasis on the Madeira, São Francisco, and Paraná river basins. For this purpose, a 10-year set of 6-month range seasonal hindcasts was produced using the Eta Regional Climate Model at 20-km horizontal resolution driven by the CFSv2 forecasts. In addition to dynamical downscaling, the precipitation and 2-meter temperature were statistically downscaled by applying a Quantile Mapping bias correction. The Eta model forecasts reasonably reproduced the precipitation and temperature patterns in the region, with some errors that were reduced by the statistical downscaling. Precipitation skill scores are higher in the northern and central areas of the continent. Although it has shown mixed performance for extreme events—low in the Paraná basin and limited but useful in the Madeira and São Francisco basins—the dynamical-statistical system developed with the Eta model shows higher skill and added value over the driver model, indicating potential to support water resources management in South America.

Keywords:
Bias correction; Climate extremes; Brazilian river basins; Forecast errors; Eta model