Summer drought predictability over Europe: empirical versus dynamical forecasts

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabili...

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Bibliographic Details
Published in:Environmental research letters 2017-08, Vol.12 (8), p.84006
Main Authors: Turco, Marco, Ceglar, Andrej, Prodhomme, Chloé, Soret, Albert, Toreti, Andrea, Doblas-Reyes Francisco, J
Format: Article
Language:English
Subjects:
Climate
Climatologia
Drought
Energies
Environmental risk
Evapotranspiration
Historical account
Hydrologic data
Initial conditions
Predictions
Previsió del temps
Risk management
Seasonal climate forecasting
seasonal forecasts
Seasonal forectast
standardized precipitation evapotranspiration index (SPEI)
Stream discharge
Stream flow
Summer
Weather forecasting
Àrees temàtiques de la UPC
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Summary:Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts-System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.
ISSN:1748-9326
1748-9326
DOI:10.1088/1748-9326/aa7859