Upgrade of a climate service tailored to water reservoirs management

We present the upgrade of a web tool designed to help in the decision making process for water reservoirs management in Spain. The tool, called S-ClimWaRe (Seasonal Climate predictions in support of Water Reservoirs management), covers the extended winter season (from November to March), when the No...

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Bibliographic Details
Published in:Climate Services
Main Authors: E. Sánchez-García, I. Abia, M. Domínguez, J. Voces, J.C. Sánchez, B. Navascués, E. Rodríguez-Camino, M.N. Garrido, M.C. García, F. Pastor, M. Dimas, L. Barranco, C. Ruiz Del Portal
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2022
Subjects:
Reservoir management
Hydrological hazard
Seasonal prediction
Climate service
NAO
Web tool
Meteorology. Climatology
QC851-999
Social sciences (General)
H1-99
North Atlantic
North Atlantic oscillation
Online Access:https://doi.org/10.1016/j.cliser.2021.100281
https://doaj.org/article/6de4ae2ba2af46b7a619bdf2f0ee3775
Description
Summary:We present the upgrade of a web tool designed to help in the decision making process for water reservoirs management in Spain. The tool, called S-ClimWaRe (Seasonal Climate predictions in support of Water Reservoirs management), covers the extended winter season (from November to March), when the North Atlantic Oscillation (NAO) pattern strongly influences the hydrological interannual variability in South-Western Europe. This climate service is fully user driven, and aims at meeting their requirements incorporating recent scientific progress.The latest S-ClimWaRe version includes some technical enhancements requested by customers and new seasonal predictions obtained through application of two postprocessing steps to ECMWF System-5 forecasts: a downscaling statistical procedure, and a new methodology that improves the forecast skill of hydrological variables through an enhanced prediction of the winter NAO. The new version enriches the forecasting panel of the web tool with precipitation forecast skill, and provides additional forecasts for accumulated snowfall and temperature. Water reservoir inflow forecasts are generated by a hybrid statistical system and are also skilful in areas influenced by the NAO pattern. In regions not directly affected by this climate driver, a revision of this simple impact model seems to be needed. A prototype based on two different hydrological models has been tested over a pilot reservoir. The assessment of this downscaling procedure shows promising results with respect to the existing seasonal forecasts based on the statistical approach relying on the predicted NAO index.

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