Articles | Volume 21, issue 11
Hydrol. Earth Syst. Sci., 21, 5747–5762, 2017
https://doi.org/10.5194/hess-21-5747-2017

Special issue: Sub-seasonal to seasonal hydrological forecasting

Hydrol. Earth Syst. Sci., 21, 5747–5762, 2017
https://doi.org/10.5194/hess-21-5747-2017
Research article
22 Nov 2017
Research article | 22 Nov 2017

Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

Rachel Bazile et al.

Related authors

Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II
Jing Xu, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 26, 1001–1017, https://doi.org/10.5194/hess-26-1001-2022,https://doi.org/10.5194/hess-26-1001-2022, 2022
Short summary
Large-scale snow data assimilation using a spatialized particle filter: recovering the spatial structure of the particles
Jean Odry, Marie-Amélie Boucher, Simon Lachance-Cloutier, Richard Turcotte, and Pierre-Yves St-Louis
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-322,https://doi.org/10.5194/tc-2021-322, 2021
Revised manuscript accepted for TC
Short summary
Investigating ANN architectures and training to estimate snow water equivalent from snow depth
Konstantin F. F. Ntokas, Jean Odry, Marie-Amélie Boucher, and Camille Garnaud
Hydrol. Earth Syst. Sci., 25, 3017–3040, https://doi.org/10.5194/hess-25-3017-2021,https://doi.org/10.5194/hess-25-3017-2021, 2021
Short summary
Assessing the capabilities of the Surface Water and Ocean Topography (SWOT) mission for large lake water surface elevation monitoring under different wind conditions
Jean Bergeron, Gabriela Siles, Robert Leconte, Mélanie Trudel, Damien Desroches, and Daniel L. Peters
Hydrol. Earth Syst. Sci., 24, 5985–6000, https://doi.org/10.5194/hess-24-5985-2020,https://doi.org/10.5194/hess-24-5985-2020, 2020
Short summary
Modelling of shallow water table dynamics using conceptual and physically based integrated surface-water–groundwater hydrologic models
Mohammad Bizhanimanzar, Robert Leconte, and Mathieu Nuth
Hydrol. Earth Syst. Sci., 23, 2245–2260, https://doi.org/10.5194/hess-23-2245-2019,https://doi.org/10.5194/hess-23-2245-2019, 2019
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Uncertainty analysis
Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning
Lei Xu, Nengcheng Chen, Chao Yang, Hongchu Yu, and Zeqiang Chen
Hydrol. Earth Syst. Sci., 26, 2923–2938, https://doi.org/10.5194/hess-26-2923-2022,https://doi.org/10.5194/hess-26-2923-2022, 2022
Short summary
Unraveling the contribution of potential evaporation formulation to uncertainty under climate change
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel, and Lila Collet
Hydrol. Earth Syst. Sci., 26, 2147–2159, https://doi.org/10.5194/hess-26-2147-2022,https://doi.org/10.5194/hess-26-2147-2022, 2022
Short summary
Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II
Jing Xu, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 26, 1001–1017, https://doi.org/10.5194/hess-26-1001-2022,https://doi.org/10.5194/hess-26-1001-2022, 2022
Short summary
Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems
Emixi Sthefany Valdez, François Anctil, and Maria-Helena Ramos
Hydrol. Earth Syst. Sci., 26, 197–220, https://doi.org/10.5194/hess-26-197-2022,https://doi.org/10.5194/hess-26-197-2022, 2022
Short summary
Performance of the Global Forecast System's medium-range precipitation forecasts in the Niger river basin using multiple satellite-based products
Haowen Yue, Mekonnen Gebremichael, and Vahid Nourani
Hydrol. Earth Syst. Sci., 26, 167–181, https://doi.org/10.5194/hess-26-167-2022,https://doi.org/10.5194/hess-26-167-2022, 2022
Short summary

Cited articles

Bröcker, J. and Smith, L. A.: From ensemble forecasts to predictive distribution functions, Tellus A, 60, 663–678, 2008.
Cloke, H. and Pappenberger, F.: Ensemble flood forecasting: a review, J. Hydrol., 375, 613–626, 2009.
Crochemore, L., Ramos, M.-H., and Pappenberger, F.: Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts, Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, 2016.
Day, G. N.: Extended streamflow forecasting using NWSRFS, J. Water Res. Plan. Man., 111, 157–170, 1985.
DelSole, T.: Predictability and information theory. Part I: Measures of predictability, J. Atmos. Sci., 61, 2425–2440, 2004.
Download
Short summary
Meteorological forecasting agencies constantly work on pushing the limit of predictability farther in time. However, some end users need proof that climate model outputs are ready to be implemented operationally. We show that bias correction is crucial for the use of ECMWF System4 forecasts for the studied area and there is a potential for the use of 1-month-ahead forecasts. Beyond this, forecast performance is equivalent to using past climatology series as inputs to the hydrological model.