Articles | Volume 20, issue 10
https://doi.org/10.5194/hess-20-4283-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-4283-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Oct 2016
Research article |
| 21 Oct 2016
Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin
GFZ German Research Centre for Geosciences, Potsdam, Germany
Gerd Bürger
Institute of Meteorology, FU Berlin, Germany
Institute of Earth and Environmental Science, University of Potsdam, Germany
Sergiy Vorogushyn
GFZ German Research Centre for Geosciences, Potsdam, Germany
Bruno Merz
GFZ German Research Centre for Geosciences, Potsdam, Germany
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Cited
16 citations as recorded by crossref.
- Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes A. Murawski et al. 10.1002/2017JD026654
- Winter particulate pollution severity in North China driven by atmospheric teleconnections J. Li et al. 10.1038/s41561-022-00933-2
- Synchronization and Delay Between Circulation Patterns and High Streamflow Events in Germany F. Conticello et al. 10.1029/2019WR025598
- Tailoring circulation type classification outcomes F. Hansen & D. Belušić 10.1002/joc.7171
- Downscaling daily wind speed with Bayesian deep learning for climate monitoring F. Gerges et al. 10.1007/s41060-023-00397-6
- Weather Typing‐Based Flood Frequency Analysis Verified for Exceptional Historical Events of Past 500 Years Along the Meuse River J. De Niel et al. 10.1002/2017WR020803
- Reliable Future Climatic Projections for Sustainable Hydro-Meteorological Assessments in the Western Lake Erie Basin S. Mehan et al. 10.3390/w11030581
- An event synchronization method to link heavy rainfall events and large‐scale atmospheric circulation features F. Conticello et al. 10.1002/joc.5255
- Systemic change in the Rhine-Meuse basin: Quantifying and explaining parameters trends in the PCR-GLOBWB global hydrological model J. Ruijsch et al. 10.1016/j.advwatres.2021.104013
- Deep Learning-Based Downscaling of Temperatures for Monitoring Local Climate Change Using Global Climate Simulation Data F. Gerges et al. 10.1142/S2811032322500011
- Potential Predictability of Regional Precipitation and Discharge Extremes Using Synoptic-Scale Climate Information via Machine Learning: An Evaluation for the Eastern Continental United States J. Knighton et al. 10.1175/JHM-D-18-0196.1
- Changes in French weather pattern seasonal frequencies projected by a CMIP5 ensemble P. Brigode et al. 10.1002/joc.5549
- A non-stationary climate-informed weather generator for assessing future flood risks V. Nguyen et al. 10.5194/ascmo-10-195-2024
- Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products J. Delgado et al. 10.5194/hess-22-5041-2018
- Causative classification of river flood events L. Tarasova et al. 10.1002/wat2.1353
- Past and Projected Weather Pattern Persistence with Associated Multi-Hazards in the British Isles P. De Luca et al. 10.3390/atmos10100577
16 citations as recorded by crossref.
- Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes A. Murawski et al. 10.1002/2017JD026654
- Winter particulate pollution severity in North China driven by atmospheric teleconnections J. Li et al. 10.1038/s41561-022-00933-2
- Synchronization and Delay Between Circulation Patterns and High Streamflow Events in Germany F. Conticello et al. 10.1029/2019WR025598
- Tailoring circulation type classification outcomes F. Hansen & D. Belušić 10.1002/joc.7171
- Downscaling daily wind speed with Bayesian deep learning for climate monitoring F. Gerges et al. 10.1007/s41060-023-00397-6
- Weather Typing‐Based Flood Frequency Analysis Verified for Exceptional Historical Events of Past 500 Years Along the Meuse River J. De Niel et al. 10.1002/2017WR020803
- Reliable Future Climatic Projections for Sustainable Hydro-Meteorological Assessments in the Western Lake Erie Basin S. Mehan et al. 10.3390/w11030581
- An event synchronization method to link heavy rainfall events and large‐scale atmospheric circulation features F. Conticello et al. 10.1002/joc.5255
- Systemic change in the Rhine-Meuse basin: Quantifying and explaining parameters trends in the PCR-GLOBWB global hydrological model J. Ruijsch et al. 10.1016/j.advwatres.2021.104013
- Deep Learning-Based Downscaling of Temperatures for Monitoring Local Climate Change Using Global Climate Simulation Data F. Gerges et al. 10.1142/S2811032322500011
- Potential Predictability of Regional Precipitation and Discharge Extremes Using Synoptic-Scale Climate Information via Machine Learning: An Evaluation for the Eastern Continental United States J. Knighton et al. 10.1175/JHM-D-18-0196.1
- Changes in French weather pattern seasonal frequencies projected by a CMIP5 ensemble P. Brigode et al. 10.1002/joc.5549
- A non-stationary climate-informed weather generator for assessing future flood risks V. Nguyen et al. 10.5194/ascmo-10-195-2024
- Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products J. Delgado et al. 10.5194/hess-22-5041-2018
- Causative classification of river flood events L. Tarasova et al. 10.1002/wat2.1353
- Past and Projected Weather Pattern Persistence with Associated Multi-Hazards in the British Isles P. De Luca et al. 10.3390/atmos10100577
Latest update: 24 Apr 2025
Short summary
To understand past flood changes in the Rhine catchment and the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. Here the link between patterns and local climate is tested, and the skill of GCMs in reproducing these patterns is evaluated.
To understand past flood changes in the Rhine catchment and the role of anthropogenic climate...
