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A summer of science using GloFAS

Summer 2019 has been a busy time for GloFAS research. Across June and July 2019 five papers using GloFAS data have been published in international scientific journals spanning diverse topics. Ervin Zsoter from the European Centre for Medium-Range Weather Forecasts (ECMWF) critiques the ability of the current generation of land-surface models, as used operationally in GloFAS, to fully represent hydrology and identified key weaknesses in the land data assimilation scheme for conserving the water budget in Zsoter et al. (2019). Andrea Ficchì and Liz Stephens from the University of Reading in the UK use GloFAS river discharge reanalysis data across sub‐Saharan Africa to examine how modes of climate variability, such as the Indian Ocean Dipole and El Niño–Southern Oscillation, alter the timing of floods in Ficchì and Stephens (2019). Another study from the University of Reading by Jamie Towner presents an intercomparison of eight different global hydrological models freely available from collaborators within the Global Flood Partnership (GFP), in which GloFAS is part of, for capturing peak river flows in the Amazon basin in Towner et al. (2019). Konstantinos Bischiniotis from the Institute for Environmental Studies (IVM) in the Netherlands published two papers over the summer: Bischiniotis et al. (2019a) assesses the skill of GloFAS flood forecasts across Peru over 2009 to 2015, a region where GloFAS is being used operationally by the Red Cross, and Bischiniotis et al. (2019b) develops a methodology to assess the potential added value of early warning action systems for forecast-based financing for floods, using GloFAS as a case study system in Uganda.

 

There are more GloFAS papers in the pipeline for later in 2019/2020 so stay tuned! GloFAS river discharge reanalysis and forecast data are made freely available to everyone as part of the Copernicus Emergency Management Service (CEMS), so if you would like to use GloFAS data then please send your request to: info@globalfloods.eu. Details on the available datasets can be found on the GloFAS website here.

 

Full references

Bischiniotis, K., van den Hurk, B., Zsoter, E., Perez, E. C. de, Grillakis, M. and Aerts, J. C. J. H.: Evaluation of a global ensemble flood prediction system in Peru, Hydrological Sciences Journal, 64(10), 1171–1189, doi:10.1080/02626667.2019.1617868, 2019a.

Bischiniotis, K., van den Hurk, B., Coughlan de Perez, E., Veldkamp, T., Nobre, G. G. and Aerts, J.: Assessing time, cost and quality trade-offs in forecast-based action for floods, International Journal of Disaster Risk Reduction, 40, 101252, doi:10.1016/j.ijdrr.2019.101252, 2019b.

Ficchì, A. and Stephens, L.: Climate Variability Alters Flood Timing Across Africa, Geophysical Research Letters, 46, doi:10.1029/2019GL081988, 2019.

Towner, J., Cloke, H. L., Zsoter, E., Flamig, Z., Hoch, J. M., Bazo, J., Coughlan de Perez, E. and Stephens, E. M.: Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin, Hydrology and Earth System Sciences, 23(7), 3057–3080, doi:https://doi.org/10.5194/hess-23-3057-2019, 2019.

Zsoter, E., Cloke, H., Stephens, E., de Rosnay, P., Muñoz-Sabater, J., Prudhomme, C. and Pappenberger, F.: How Well Do Operational Numerical Weather Prediction Configurations Represent Hydrology?, J. Hydrometeor., 20(8), 1533–1552, doi:10.1175/JHM-D-18-0086.1, 2019.


By Shaun Harrigan     Aug. 20, 2019, 10:08 a.m.