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The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (Bß) and the relative operating characteristic skill score (ROCß). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with Bß. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and Bß and significant skill when discriminating hit rate and false alarm rate given by the ROCß (forecasting drought events of, e.g., SPEI1 showed a ROCß of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil. © Author(s) 2018.