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Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0

Emerton, R., Zsoter, E., Arnal, L., Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X, Muraro, D., Prudhomme, C., Stephens, E. M. ORCID: https://orcid.org/0000-0002-5439-7563, Salamon, P. and Pappenberger, F. (2018) Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0. Geoscientific Model Development, 11. pp. 3327-3346. ISSN 1991-9603

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To link to this item DOI: 10.5194/gmd-11-3327-2018

Abstract/Summary

Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-meteorological forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other forecasting system exists. We describe the key hydro-meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary Research Centres (IDRCs) > Walker Institute
Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:78570
Publisher:European Geosciences Union

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