Articles | Volume 22, issue 12
https://doi.org/10.5194/hess-22-6591-2018
© Author(s) 2018. 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-22-6591-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Dec 2018
Research article |
| 21 Dec 2018
| 21 Dec 2018
On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark
Diana Lucatero
CORRESPONDING AUTHOR
Department of Geosciences and Natural Resource Management, University
of Copenhagen, Copenhagen, Denmark
Henrik Madsen
DHI, Hørsholm, Denmark
Jens C. Refsgaard
Geological Survey of Denmark and Greenland (GEUS), Copenhagen,
Denmark
Jacob Kidmose
Geological Survey of Denmark and Greenland (GEUS), Copenhagen,
Denmark
Karsten H. Jensen
Department of Geosciences and Natural Resource Management, University
of Copenhagen, Copenhagen, Denmark
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Cited
15 citations as recorded by crossref.
- 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
- Evaluation of the potential of using subsets of historical climatological data for ensemble streamflow prediction (ESP) forecasting B. Sabzipour et al. 10.1016/j.jhydrol.2020.125656
- The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter? D. Anghileri et al. 10.1029/2019WR025280
- Probabilistic post-processing of short to medium range temperature forecasts: Implications for heatwave prediction in India S. Saminathan & S. Mitra 10.1007/s10661-024-12418-3
- 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
- Quantification of macropore flow in Danish soils using near-saturated hydraulic properties A. Kotlar et al. 10.1016/j.geoderma.2020.114479
- Calibrating anomalies improves forecasting of daily reference crop evapotranspiration Q. Yang et al. 10.1016/j.jhydrol.2022.128009
- Evaluation of sub-seasonal to seasonal rainfall forecast over Zambia B. Musonda et al. 10.1007/s12040-020-01548-0
- Post-processing of hydrological model simulations using the convolutional neural network and support vector regression S. Liu et al. 10.2166/nh.2022.004
- Seasonal streamflow forecasting by surrogate modeling in the Yarlung Zangbo River Basin, China H. Gu et al. 10.1016/j.ejrh.2024.101835
- Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran M. Nobakht et al. 10.1007/s00376-020-0025-7
- Seasonal Climate Forecast Skill Assessment for the Management of Water Resources in a Run of River Hydropower System in the Poqueira River (Southern Spain) E. Contreras et al. 10.3390/w12082119
- Sub seasonal streamflow forecast assessment at large-scale basins E. Schmitt Quedi & F. Mainardi Fan 10.1016/j.jhydrol.2020.124635
- Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. 10.5194/hess-22-3601-2018
- Deterministic and probabilistic evaluation of raw and post processed sub-seasonal to seasonal precipitation forecasts in different precipitation regimes R. Kolachian & B. Saghafian 10.1007/s00704-018-2680-5
13 citations as recorded by crossref.
- 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
- Evaluation of the potential of using subsets of historical climatological data for ensemble streamflow prediction (ESP) forecasting B. Sabzipour et al. 10.1016/j.jhydrol.2020.125656
- The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter? D. Anghileri et al. 10.1029/2019WR025280
- Probabilistic post-processing of short to medium range temperature forecasts: Implications for heatwave prediction in India S. Saminathan & S. Mitra 10.1007/s10661-024-12418-3
- 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
- Quantification of macropore flow in Danish soils using near-saturated hydraulic properties A. Kotlar et al. 10.1016/j.geoderma.2020.114479
- Calibrating anomalies improves forecasting of daily reference crop evapotranspiration Q. Yang et al. 10.1016/j.jhydrol.2022.128009
- Evaluation of sub-seasonal to seasonal rainfall forecast over Zambia B. Musonda et al. 10.1007/s12040-020-01548-0
- Post-processing of hydrological model simulations using the convolutional neural network and support vector regression S. Liu et al. 10.2166/nh.2022.004
- Seasonal streamflow forecasting by surrogate modeling in the Yarlung Zangbo River Basin, China H. Gu et al. 10.1016/j.ejrh.2024.101835
- Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran M. Nobakht et al. 10.1007/s00376-020-0025-7
- Seasonal Climate Forecast Skill Assessment for the Management of Water Resources in a Run of River Hydropower System in the Poqueira River (Southern Spain) E. Contreras et al. 10.3390/w12082119
- Sub seasonal streamflow forecast assessment at large-scale basins E. Schmitt Quedi & F. Mainardi Fan 10.1016/j.jhydrol.2020.124635
2 citations as recorded by crossref.
- Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. 10.5194/hess-22-3601-2018
- Deterministic and probabilistic evaluation of raw and post processed sub-seasonal to seasonal precipitation forecasts in different precipitation regimes R. Kolachian & B. Saghafian 10.1007/s00704-018-2680-5
Latest update: 20 Nov 2024
Short summary
The present study evaluates the skill of a seasonal forecasting system for hydrological relevant variables in Denmark. Linear scaling and quantile mapping were used to correct the forecasts. Uncorrected forecasts tend to be more skillful than climatology, in general, for the first month lead time only. Corrected forecasts show a reduced bias in the mean; are more consistent; and show a level of accuracy that is closer to, although no higher than, that of ensemble climatology, in general.
The present study evaluates the skill of a seasonal forecasting system for hydrological relevant...
Special issue