Forecasting annual maximum water level for the Negro River at Manaus using dynamical seasonal predictions

Early and skilful prediction of the Negro River maximum water levels at Manaus is critical for effective mitigation measures to safeguard lives livelihoods. Using dynamical seasonal hindcasts, from six centres, we investigate extending lead time previously developed statistical models, which issue forecasts in March Manaus. The original forecast models used observed rainfall as major predictor. We advance capability earlier, February. develop ensemble by combining predictor data observations hindcasts. compare those against using climatology or persistence predictors. ensemble-mean forecasts, issued February, European Centre Medium-Range Weather Forecasts (ECMWF) hindcast input, perform similarly gain one month time. ECMWF-based skilfully predict likelihood exceeding severe flood level 29 m. Forecast performance reduces spread increases with increasing February January. conclude that can be produced combined input real-time ECMWF forecasts.