Articles | Volume 20, issue 9
https://doi.org/10.5194/hess-20-3601-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-20-3601-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts
Louise Crochemore
CORRESPONDING AUTHOR
Irstea, Hydrosystems and Bioprocesses Research Unit, 1 rue Pierre Gilles de Gennes, 92 761, Antony, France
now at: Swedish Meteorological and Hydrological Institute (SMHI), Norrköping,
Sweden
Maria-Helena Ramos
Irstea, Hydrosystems and Bioprocesses Research Unit, 1 rue Pierre Gilles de Gennes, 92 761, Antony, France
Florian Pappenberger
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
School of Geographical Sciences, University of Bristol, University Road, Bristol, BS8 1SS, UK
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- Subseasonal hydrometeorological ensemble predictions in small- and medium-sized mountainous catchments: benefits of the NWP approach S. Monhart et al. 10.5194/hess-23-493-2019
- Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale? L. Crochemore et al. 10.1029/2019WR025700
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- Climate change impact on flood hazard over Italy M. García-Valdecasas Ojeda et al. 10.1016/j.jhydrol.2022.128628
- Comparing Bias Correction Methods Used in Downscaling Precipitation and Temperature from Regional Climate Models: A Case Study from the Kaidu River Basin in Western China M. Luo et al. 10.3390/w10081046
- Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems E. Valdez et al. 10.5194/hess-26-197-2022
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Evaluation of ECMWF mid-range ensemble forecasts of precipitation for the Karun River basin M. Abedi et al. 10.1007/s00704-020-03160-0
- The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter? D. Anghileri et al. 10.1029/2019WR025280
- Advances in the Definition of Needs and Specifications for a Climate Service Tool Aimed at Small Hydropower Plants’ Operation and Management E. Contreras et al. 10.3390/en13071827
- 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
- How does the quantification of uncertainties affect the quality and value of flood early warning systems? A. Thiboult et al. 10.1016/j.jhydrol.2017.05.014
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Short summary
This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
This study investigates the way bias correcting precipitation forecasts can improve the skill of...
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