Articles | Volume 21, issue 11
https://doi.org/10.5194/hess-21-5747-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-21-5747-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Nov 2017
Research article |
| 22 Nov 2017
| 22 Nov 2017
Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate
Rachel Bazile
CORRESPONDING AUTHOR
Département de génie civil, Université de Sherbrooke, 2500
Boul. de l'Université, Sherbrooke, Québec, J1R 2R2,
Canada
Invited contribution by Rachel Bazile, recipient of the EGU Hydrological Sciences Outstanding Student Poster and PICO Award 2017.
Marie-Amélie Boucher
Département de génie civil, Université de Sherbrooke, 2500
Boul. de l'Université, Sherbrooke, Québec, J1R 2R2,
Canada
Luc Perreault
Institut de Recherche d'Hydro-Québec (IREQ), 1800 boul.
Lionel-Boulet, Varennes, Québec, J3X 1S1, Canada
Robert Leconte
Département de génie civil, Université de Sherbrooke, 2500
Boul. de l'Université, Sherbrooke, Québec, J1R 2R2,
Canada
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Cited
21 citations as recorded by crossref.
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- Seasonal forecasts offer economic benefit for hydrological decision making in semi-arid regions T. Portele et al. 10.1038/s41598-021-89564-y
- A global 30-m ET model (HSEB) using harmonized Landsat and Sentinel-2, MODIS and VIIRS: Comparison to ECOSTRESS ET and LST H. Jaafar et al. 10.1016/j.rse.2022.112995
- Smart Climate Hydropower Tool: A Machine-Learning Seasonal Forecasting Climate Service to Support Cost–Benefit Analysis of Reservoir Management A. Essenfelder et al. 10.3390/atmos11121305
- Hydropower System Operation and the Quality of Short-Term Hydrologic Ensemble Forecasts M. Osina Torres et al. 10.1061/JWRMD5.WRENG-5608
- Deterministic and probabilistic evaluation of raw and post-processing monthly precipitation forecasts: a case study of China Y. Li et al. 10.2166/hydro.2021.176
- Sub seasonal streamflow forecast assessment at large-scale basins E. Schmitt Quedi & F. Mainardi Fan 10.1016/j.jhydrol.2020.124635
- Usability of weather information services for decision-making in farming: Evidence from the Ada East District, Ghana R. Sarku et al. 10.1016/j.cliser.2021.100275
- Seasonal streamflow forecasts for Europe – Part 2: Sources of skill W. Greuell et al. 10.5194/hess-23-371-2019
- Seasonal Streamflow Forecast in the Tocantins River Basin, Brazil: An Evaluation of ECMWF-SEAS5 with Multiple Conceptual Hydrological Models L. Ávila et al. 10.3390/w15091695
- Sources of skill in lake temperature, discharge and ice-off seasonal forecasting tools F. Clayer et al. 10.5194/hess-27-1361-2023
- Examining controls on peak annual streamflow and floods in the Fraser River Basin of British Columbia C. Curry & F. Zwiers 10.5194/hess-22-2285-2018
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Forecasting water temperature in lakes and reservoirs using seasonal climate prediction D. Mercado-Bettín et al. 10.1016/j.watres.2021.117286
- The benefit of seamless forecasts for hydrological predictions over Europe F. Wetterhall & F. Di Giuseppe 10.5194/hess-22-3409-2018
- A Global Implementation of Single‐ and Dual‐Source Surface Energy Balance Models for Estimating Actual Evapotranspiration at 30‐m Resolution Using Google Earth Engine H. Jaafar et al. 10.1029/2022WR032800
- Coupling forecast calibration and data‐driven downscaling for generating reliable, high‐resolution, multivariate seasonal climate forecast ensembles at multiple sites A. Schepen et al. 10.1002/joc.6346
- Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times S. Donegan et al. 10.5194/hess-25-4159-2021
- Mapping shoreline change using machine learning: a case study from the eastern Indian coast L. Kumar et al. 10.1007/s11600-020-00454-9
- Impact of Geology on Seasonal Hydrological Predictability in Alpine Regions by a Sensitivity Analysis Framework M. Stergiadi et al. 10.3390/w12082255
- Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe N. Mishra et al. 10.1007/s00382-018-4404-z
20 citations as recorded by crossref.
- Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK A. Peñuela et al. 10.5194/hess-24-6059-2020
- Seasonal forecasts offer economic benefit for hydrological decision making in semi-arid regions T. Portele et al. 10.1038/s41598-021-89564-y
- A global 30-m ET model (HSEB) using harmonized Landsat and Sentinel-2, MODIS and VIIRS: Comparison to ECOSTRESS ET and LST H. Jaafar et al. 10.1016/j.rse.2022.112995
- Smart Climate Hydropower Tool: A Machine-Learning Seasonal Forecasting Climate Service to Support Cost–Benefit Analysis of Reservoir Management A. Essenfelder et al. 10.3390/atmos11121305
- Hydropower System Operation and the Quality of Short-Term Hydrologic Ensemble Forecasts M. Osina Torres et al. 10.1061/JWRMD5.WRENG-5608
- Deterministic and probabilistic evaluation of raw and post-processing monthly precipitation forecasts: a case study of China Y. Li et al. 10.2166/hydro.2021.176
- Sub seasonal streamflow forecast assessment at large-scale basins E. Schmitt Quedi & F. Mainardi Fan 10.1016/j.jhydrol.2020.124635
- Usability of weather information services for decision-making in farming: Evidence from the Ada East District, Ghana R. Sarku et al. 10.1016/j.cliser.2021.100275
- Seasonal streamflow forecasts for Europe – Part 2: Sources of skill W. Greuell et al. 10.5194/hess-23-371-2019
- Seasonal Streamflow Forecast in the Tocantins River Basin, Brazil: An Evaluation of ECMWF-SEAS5 with Multiple Conceptual Hydrological Models L. Ávila et al. 10.3390/w15091695
- Sources of skill in lake temperature, discharge and ice-off seasonal forecasting tools F. Clayer et al. 10.5194/hess-27-1361-2023
- Examining controls on peak annual streamflow and floods in the Fraser River Basin of British Columbia C. Curry & F. Zwiers 10.5194/hess-22-2285-2018
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Forecasting water temperature in lakes and reservoirs using seasonal climate prediction D. Mercado-Bettín et al. 10.1016/j.watres.2021.117286
- The benefit of seamless forecasts for hydrological predictions over Europe F. Wetterhall & F. Di Giuseppe 10.5194/hess-22-3409-2018
- A Global Implementation of Single‐ and Dual‐Source Surface Energy Balance Models for Estimating Actual Evapotranspiration at 30‐m Resolution Using Google Earth Engine H. Jaafar et al. 10.1029/2022WR032800
- Coupling forecast calibration and data‐driven downscaling for generating reliable, high‐resolution, multivariate seasonal climate forecast ensembles at multiple sites A. Schepen et al. 10.1002/joc.6346
- Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times S. Donegan et al. 10.5194/hess-25-4159-2021
- Mapping shoreline change using machine learning: a case study from the eastern Indian coast L. Kumar et al. 10.1007/s11600-020-00454-9
- Impact of Geology on Seasonal Hydrological Predictability in Alpine Regions by a Sensitivity Analysis Framework M. Stergiadi et al. 10.3390/w12082255
1 citations as recorded by crossref.
Saved (final revised paper)
Latest update: 23 Apr 2024
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.
Meteorological forecasting agencies constantly work on pushing the limit of predictability...
Special issue