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Volume 22, issue 9 | Copyright
Hydrol. Earth Syst. Sci., 22, 5041-5056, 2018
https://doi.org/10.5194/hess-22-5041-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 28 Sep 2018

Research article | 28 Sep 2018

Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products

José Miguel Delgado1, Sebastian Voss1, Gerd Bürger1, Klaus Vormoor1, Aline Murawski2, José Marcelo Rodrigues Pereira3, Eduardo Martins3, Francisco Vasconcelos Júnior3, and Till Francke1 José Miguel Delgado et al.
  • 1Institute of Earth and Environmental Sciences, University of Potsdam, Potsdam, Germany
  • 2German Research Centre of Geosciences GFZ Potsdam, Potsdam, Germany
  • 3Research Institute for Meteorology and Water Resources – FUNCEME, Fortaleza, Brazil

Abstract. A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará's research foundation for meteorology) and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation, (b) meteorological drought indices, and (c) hydrological drought indices.

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.

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The feasibility of drought prediction is assessed in the Brazilian northeast. The models were provided by a regional agency and a European meteorological agency and downscaling was done using three empirical models. This work showed that the combination of different forecast and downscaling models can provide skillful predictions of drought events on timescales relevant to water managers. But the models also showed little to no skill for quantitative predictions of monthly precipitation.
The feasibility of drought prediction is assessed in the Brazilian northeast. The models were...
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