Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0
<p>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 variab...
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doaj-578a403bd7d9497ebcc23b3411b722a02020-11-25T01:28:16ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032018-08-01113327334610.5194/gmd-11-3327-2018Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0R. Emerton0R. Emerton1E. Zsoter2E. Zsoter3L. Arnal4L. Arnal5H. L. Cloke6H. L. Cloke7D. Muraro8C. Prudhomme9C. Prudhomme10C. Prudhomme11E. M. Stephens12P. Salamon13F. Pappenberger14Department of Geography & Environmental Science, University of Reading, Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading,UK Department of Geography & Environmental Science, University of Reading, Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading,UK Department of Geography & Environmental Science, University of Reading, Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading,UK Department of Geography & Environmental Science, University of Reading, Reading, UK Department of Earth Sciences, Uppsala University, Uppsala, SwedenImage Recognition Integrated Systems (IRIS), Ispra, ItalyEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading,UK Centre for Ecology and Hydrology (CEH), Wallingford, UKDepartment of Geography and Environment, University of Loughborough, Loughborough, UKDepartment of Geography & Environmental Science, University of Reading, Reading, UKEuropean Commission, Joint Research Centre (JRC), Ispra, ItalyEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading,UK <p>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.</p>https://www.geosci-model-dev.net/11/3327/2018/gmd-11-3327-2018.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
R. Emerton R. Emerton E. Zsoter E. Zsoter L. Arnal L. Arnal H. L. Cloke H. L. Cloke D. Muraro C. Prudhomme C. Prudhomme C. Prudhomme E. M. Stephens P. Salamon F. Pappenberger |
spellingShingle |
R. Emerton R. Emerton E. Zsoter E. Zsoter L. Arnal L. Arnal H. L. Cloke H. L. Cloke D. Muraro C. Prudhomme C. Prudhomme C. Prudhomme E. M. Stephens P. Salamon F. Pappenberger Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 Geoscientific Model Development |
author_facet |
R. Emerton R. Emerton E. Zsoter E. Zsoter L. Arnal L. Arnal H. L. Cloke H. L. Cloke D. Muraro C. Prudhomme C. Prudhomme C. Prudhomme E. M. Stephens P. Salamon F. Pappenberger |
author_sort |
R. Emerton |
title |
Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 |
title_short |
Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 |
title_full |
Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 |
title_fullStr |
Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 |
title_full_unstemmed |
Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 |
title_sort |
developing a global operational seasonal hydro-meteorological forecasting system: glofas-seasonal v1.0 |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2018-08-01 |
description |
<p>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.</p> |
url |
https://www.geosci-model-dev.net/11/3327/2018/gmd-11-3327-2018.pdf |
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