Refining Seasonal Precipitation Forecast in Brazil Using Simple Data-Driven Techniques and Climate Indices
Published in Revista Brasileira de Meteorologia , 2024
Recommended citation: Torres, F. L. R., Kuki, C. A. C., Reboita, M. S., Lima, L. M. M., Lima, J. W. M., & Queiroz, A. R. D. (2024). Refining Seasonal Precipitation Forecast in Brazil Using Simple Data-Driven Techniques and Climate Indices. Revista Brasileira de Meteorologia, 39, e39240052. https://doi.org/10.1590/0102-77863910052
These models employ climate indices related to different teleconnection patterns that affect seasonal precipitation in Brazil, the unified gauge-based analysis of global daily precipitation from the Climate Prediction Center (CPC), and the precipitation forecasts from the Seasonal Forecast System 5 (SEAS5) as input variables. Both MLR and SVM models were validated from Jan-2017 to Dec-2020 using precipitation from the CPC as ground truth. The results suggest that, compared to SEAS5, MLR and SVM models enhance predictive accuracy and reduce bias in precipitation forecasts for the Southeast, Midwest, and North regions of Brazil during the austral summer. However, the performance of the models was found to be on par with the original predictions of SEAS5 in the Northeast and South regions, sectors of Brazil where the climate is significantly influenced by the El Niño-Southern Oscillation.