Articles | Volume 11, issue 8
https://doi.org/10.5194/gmd-11-3327-2018
https://doi.org/10.5194/gmd-11-3327-2018
Development and technical paper
 | Highlight paper
 | 
21 Aug 2018
Development and technical paper | Highlight paper |  | 21 Aug 2018

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

Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger

Related authors

Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity
Jessica L. Neumann, Louise Arnal, Rebecca E. Emerton, Helen Griffith, Stuart Hyslop, Sofia Theofanidi, and Hannah L. Cloke
Geosci. Commun., 1, 35–57, https://doi.org/10.5194/gc-1-35-2018,https://doi.org/10.5194/gc-1-35-2018, 2018
Short summary

Related subject area

Hydrology
Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL)
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024,https://doi.org/10.5194/gmd-17-7181-2024, 2024
Short summary
PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration
Matevž Vremec, Raoul A. Collenteur, and Steffen Birk
Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024,https://doi.org/10.5194/gmd-17-7083-2024, 2024
Short summary
Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks
Nedal Aqel, Lea Reusser, Stephan Margreth, Andrea Carminati, and Peter Lehmann
Geosci. Model Dev., 17, 6949–6966, https://doi.org/10.5194/gmd-17-6949-2024,https://doi.org/10.5194/gmd-17-6949-2024, 2024
Short summary
Regionalization in global hydrological models and its impact on runoff simulations: a case study using WaterGAP3 (v 1.0.0)
Jenny Kupzig, Nina Kupzig, and Martina Flörke
Geosci. Model Dev., 17, 6819–6846, https://doi.org/10.5194/gmd-17-6819-2024,https://doi.org/10.5194/gmd-17-6819-2024, 2024
Short summary
STORM v.2: A simple, stochastic rainfall model for exploring the impacts of climate and climate change at and near the land surface in gauged watersheds
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024,https://doi.org/10.5194/gmd-17-5387-2024, 2024
Short summary

Cited articles

Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. 
Arnal, L., Cloke, H. L., Stephens, E., Wetterhall, F., Prudhomme, C., Neumann, J., Krzeminski, B., and Pappenberger, F.: Skilful seasonal forecasts of streamflow over Europe?, Hydrol. Earth Syst. Sci., 22, 2057–2072, https://doi.org/10.5194/hess-22-2057-2018, 2018. 
Bahra, A.: Managing work flows with ecFlow, ECMWF Newsl., 129, 30–32 available from: https://www.ecmwf.int/sites/default/files/elibrary/2011/14594-newsletter-no129-autumn-2011.pdf (last access: 18 April 2018), 2011. 
Balsamo, G., Pappenberger, F., Dutra, E., Viterbo, P., and van den Hurk, B.: A revised land hydrology in the ECMWF model: a step towards daily water flux prediction in a fully-closed water cycle, Hydrol. Process., 25, 1046–1054, https://doi.org/10.1002/hyp.7808, 2011. 
BDHI: Base de Donnees Historiques sur les Inondations, available at: http://bdhi.fr/appli/web/welcome, last access: 23 April 2018. 
Download
Short summary
Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.