Intraseasonal Ensemble Forecasting for the Brazilian Northeastern

Authors

DOI:

https://doi.org/10.5902/2179460X35807

Keywords:

Intraseasonal climate forecast, Regional climate model, Dynamical ensemble forecast

Abstract

This preliminary analysis, uses simulations performed by the National Centers for Environmental Prediction (NCEP) coupled forecast system model version 2 (CFSv2) /regional climate model RegCM-4.6, allowed to be observed in this work, the data analyzed were the information of the surface wind intensity, by the analysis and comparison of the simulations carried out for the Alcântara region on the coast of the state of Maranhão. These simulations were stored in the period from February to June 2018. The analysis sought to validate with ERA5 reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). The observed result shows great potential for use of prediction ensemble techniques, since in the observed results the smallest anomalies were observed in the intraseasonal ensemble prediction to the Alcântara region in the intensity wind, in comparison to the simulation without being ensemble, presenting greater deviations and when closer to the forecast, in itself, greater deviations presented. The intraseasonal Ensemble estimation ends up filtering the terms of high frequency, being the best estimate and presenting intraseasonal predictions more balanced.

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Author Biographies

Cleber Souza Corrêa, Instituto de Aeronáutica e Espaço - IAE, São José dos Campos, SP

Pesquisador do Instituto de Controle do Espaço Aéreo (ICEA) e do Instituto de Aeronáutica e Espaço (IAE)

Fabricio Pereira Härter, Universidade Federal de Pelotas - UFPel, Pelotas, RS

Professor Associado da Universidade Federal de Pelotas (UFPel)

Gerson Luiz Camillo, Instituo Federal Catarinense, Videira, SC

Professor do Instituto Federal Catarinense nas áreas de Redes e Arquitetura de Computadores.

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Published

2019-07-16

How to Cite

Corrêa, C. S., Härter, F. P., & Camillo, G. L. (2019). Intraseasonal Ensemble Forecasting for the Brazilian Northeastern. Ciência E Natura, 41, e10. https://doi.org/10.5902/2179460X35807

Issue

Section

Meteorology

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