Articles | Volume 22, issue 2
https://doi.org/10.5194/nhess-22-677-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-677-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Mar 2022
Research article |
| 03 Mar 2022
| 03 Mar 2022
Adaptation and application of the large LAERTES-EU regional climate model ensemble for modeling hydrological extremes: a pilot study for the Rhine basin
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Lisa-Ann Kautz
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Hendrik Feldmann
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia (UEA), Norwich, United Kingdom
Martin Kadlec
Impact Forecasting, Aon, Prague, Czech Republic
Fanni D. Kelemen
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
now at: Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
Hilke S. Lentink
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Patrick Ludwig
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
Desmond Manful
Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia (UEA), Norwich, United Kingdom
Joaquim G. Pinto
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
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Lea Eisenstein, Benedikt Schulz, Joaquim G. Pinto, and Peter Knippertz
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Mesoscale high-wind features within extratropical cyclones can cause immense damage. In Part 1 of this work, we introduced RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), an objective, flexible identification tool for these wind features based on a probabilistic random forest. Here, we use RAMEFI to compile a climatology of the features over 19 extended winter seasons over western and central Europe, focusing on relative occurrence, affected areas and further characteristics.
Marie Hundhausen, Hendrik Feldmann, Natalie Laube, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 23, 2873–2893, https://doi.org/10.5194/nhess-23-2873-2023, https://doi.org/10.5194/nhess-23-2873-2023, 2023
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Alberto Caldas-Alvarez, Hendrik Feldmann, Etor Lucio-Eceiza, and Joaquim G. Pinto
Weather Clim. Dynam., 4, 543–565, https://doi.org/10.5194/wcd-4-543-2023, https://doi.org/10.5194/wcd-4-543-2023, 2023
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Marcus Breil, Annabell Weber, and Joaquim G. Pinto
Biogeosciences, 20, 2237–2250, https://doi.org/10.5194/bg-20-2237-2023, https://doi.org/10.5194/bg-20-2237-2023, 2023
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A promising strategy for mitigating burdens of heat extremes in Europe is to replace dark coniferous forests with brighter deciduous forests. The consequence of this would be reduced absorption of solar radiation, which should reduce the intensities of heat periods. In this study, we show that deciduous forests have a certain cooling effect on heat period intensities in Europe. However, the magnitude of the temperature reduction is quite small.
Daniel Gliksman, Paul Averbeck, Nico Becker, Barry Gardiner, Valeri Goldberg, Jens Grieger, Dörthe Handorf, Karsten Haustein, Alexia Karwat, Florian Knutzen, Hilke S. Lentink, Rike Lorenz, Deborah Niermann, Joaquim G. Pinto, Ronald Queck, Astrid Ziemann, and Christian L. E. Franzke
Nat. Hazards Earth Syst. Sci., 23, 2171–2201, https://doi.org/10.5194/nhess-23-2171-2023, https://doi.org/10.5194/nhess-23-2171-2023, 2023
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Wind and storms are a major natural hazard and can cause severe economic damage and cost human lives. Hence, it is important to gauge the potential impact of using indices, which potentially enable us to estimate likely impacts of storms or other wind events. Here, we review basic aspects of wind and storm generation and provide an extensive overview of wind impacts and available indices. This is also important to better prepare for future climate change and corresponding changes to winds.
Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis S. Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Kai Kornhuber, Harald Kunstmann, Joaquim G. Pinto, Kirsten Warrach-Sagi, and Elena Xoplaki
Nat. Hazards Earth Syst. Sci., 23, 1699–1718, https://doi.org/10.5194/nhess-23-1699-2023, https://doi.org/10.5194/nhess-23-1699-2023, 2023
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The objective of this study was to perform a comprehensive, multi-faceted analysis of the 2018 extreme summer in terms of heat and drought in central and northern Europe, with a particular focus on Germany. A combination of favorable large-scale conditions and locally dry soils were related with the intensity and persistence of the events. We also showed that such extremes have become more likely due to anthropogenic climate change and might occur almost every year under +2 °C of global warming.
Patrick Ludwig, Florian Ehmele, Mário J. Franca, Susanna Mohr, Alberto Caldas-Alvarez, James E. Daniell, Uwe Ehret, Hendrik Feldmann, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Michael Kunz, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 1287–1311, https://doi.org/10.5194/nhess-23-1287-2023, https://doi.org/10.5194/nhess-23-1287-2023, 2023
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Heavy precipitation in July 2021 led to widespread floods in western Germany and neighboring countries. The event was among the five heaviest precipitation events of the past 70 years in Germany, and the river discharges exceeded by far the statistical 100-year return values. Simulations of the event under future climate conditions revealed a strong and non-linear effect on flood peaks: for +2 K global warming, an 18 % increase in rainfall led to a 39 % increase of the flood peak in the Ahr river.
Mark Reyers, Stephanie Fiedler, Patrick Ludwig, Christoph Böhm, Volker Wennrich, and Yaping Shao
Clim. Past, 19, 517–532, https://doi.org/10.5194/cp-19-517-2023, https://doi.org/10.5194/cp-19-517-2023, 2023
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In this study we performed high-resolution climate model simulations for the hyper-arid Atacama Desert for the mid-Pliocene (3.2 Ma). The aim is to uncover the atmospheric processes that are involved in the enhancement of strong rainfall events during this period. We find that strong upper-level moisture fluxes (so-called moisture conveyor belts) originating in the tropical eastern Pacific are the main driver for increased rainfall in the mid-Pliocene.
Marcus Breil, Felix Krawczyk, and Joaquim G. Pinto
Earth Syst. Dynam., 14, 243–253, https://doi.org/10.5194/esd-14-243-2023, https://doi.org/10.5194/esd-14-243-2023, 2023
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We provide evidence that biogeophysical effects of afforestation can counteract the favorable biogeochemical climate effect of reduced CO2 concentrations. By changing the land surface characteristics, afforestation reduces vegetation surface temperatures, resulting in a reduced outgoing longwave radiation in summer, although CO2 concentrations are reduced. Since forests additionally absorb a lot of solar radiation due to their dark surfaces, afforestation has a total warming effect.
Susanna Mohr, Uwe Ehret, Michael Kunz, Patrick Ludwig, Alberto Caldas-Alvarez, James E. Daniell, Florian Ehmele, Hendrik Feldmann, Mário J. Franca, Christian Gattke, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Marc Scheibel, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 525–551, https://doi.org/10.5194/nhess-23-525-2023, https://doi.org/10.5194/nhess-23-525-2023, 2023
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The flood event in July 2021 was one of the most severe disasters in Europe in the last half century. The objective of this two-part study is a multi-disciplinary assessment that examines the complex process interactions in different compartments, from meteorology to hydrological conditions to hydro-morphological processes to impacts on assets and environment. In addition, we address the question of what measures are possible to generate added value to early response management.
Alberto Caldas-Alvarez, Markus Augenstein, Georgy Ayzel, Klemens Barfus, Ribu Cherian, Lisa Dillenardt, Felix Fauer, Hendrik Feldmann, Maik Heistermann, Alexia Karwat, Frank Kaspar, Heidi Kreibich, Etor Emanuel Lucio-Eceiza, Edmund P. Meredith, Susanna Mohr, Deborah Niermann, Stephan Pfahl, Florian Ruff, Henning W. Rust, Lukas Schoppa, Thomas Schwitalla, Stella Steidl, Annegret H. Thieken, Jordis S. Tradowsky, Volker Wulfmeyer, and Johannes Quaas
Nat. Hazards Earth Syst. Sci., 22, 3701–3724, https://doi.org/10.5194/nhess-22-3701-2022, https://doi.org/10.5194/nhess-22-3701-2022, 2022
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In a warming climate, extreme precipitation events are becoming more frequent. To advance our knowledge on such phenomena, we present a multidisciplinary analysis of a selected case study that took place on 29 June 2017 in the Berlin metropolitan area. Our analysis provides evidence of the extremeness of the case from the atmospheric and the impacts perspectives as well as new insights on the physical mechanisms of the event at the meteorological and climate scales.
Lea Eisenstein, Benedikt Schulz, Ghulam A. Qadir, Joaquim G. Pinto, and Peter Knippertz
Weather Clim. Dynam., 3, 1157–1182, https://doi.org/10.5194/wcd-3-1157-2022, https://doi.org/10.5194/wcd-3-1157-2022, 2022
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Mesoscale high-wind features within extratropical cyclones can cause immense damage. Here, we present RAMEFI, a novel approach to objectively identify the wind features based on a probabilistic random forest. RAMEFI enables a wide range of applications such as probabilistic predictions for the occurrence or a multi-decadal climatology of these features, which will be the focus of Part 2 of the study, with the goal of improving wind and, specifically, wind gust forecasts in the long run.
Emmanuele Russo, Bijan Fallah, Patrick Ludwig, Melanie Karremann, and Christoph C. Raible
Clim. Past, 18, 895–909, https://doi.org/10.5194/cp-18-895-2022, https://doi.org/10.5194/cp-18-895-2022, 2022
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In this study a set of simulations are performed with the regional climate model COSMO-CLM for Europe, for the mid-Holocene and pre-industrial periods. The main aim is to better understand the drivers of differences between models and pollen-based summer temperatures. Results show that a fundamental role is played by spring soil moisture availability. Additionally, results suggest that model bias is not stationary, and an optimal configuration could not be the best under different forcing.
Assaf Hochman, Francesco Marra, Gabriele Messori, Joaquim G. Pinto, Shira Raveh-Rubin, Yizhak Yosef, and Georgios Zittis
Earth Syst. Dynam., 13, 749–777, https://doi.org/10.5194/esd-13-749-2022, https://doi.org/10.5194/esd-13-749-2022, 2022
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Gaining a complete understanding of extreme weather, from its physical drivers to its impacts on society, is important in supporting future risk reduction and adaptation measures. Here, we provide a review of the available scientific literature, knowledge gaps and key open questions in the study of extreme weather events over the vulnerable eastern Mediterranean region.
Lisa-Ann Kautz, Olivia Martius, Stephan Pfahl, Joaquim G. Pinto, Alexandre M. Ramos, Pedro M. Sousa, and Tim Woollings
Weather Clim. Dynam., 3, 305–336, https://doi.org/10.5194/wcd-3-305-2022, https://doi.org/10.5194/wcd-3-305-2022, 2022
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Atmospheric blocking is associated with stationary, self-sustaining and long-lasting high-pressure systems. They can cause or at least influence surface weather extremes, such as heat waves, cold spells, heavy precipitation events, droughts or wind extremes. The location of the blocking determines where and what type of extreme event will occur. These relationships are also important for weather prediction and may change due to global warming.
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
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To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
Kim H. Stadelmaier, Patrick Ludwig, Pascal Bertran, Pierre Antoine, Xiaoxu Shi, Gerrit Lohmann, and Joaquim G. Pinto
Clim. Past, 17, 2559–2576, https://doi.org/10.5194/cp-17-2559-2021, https://doi.org/10.5194/cp-17-2559-2021, 2021
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We use regional climate simulations for the Last Glacial Maximum to reconstruct permafrost and to identify areas of thermal contraction cracking of the ground in western Europe. We find ground cracking, a precondition for the development of permafrost proxies, south of the probable permafrost border, implying that permafrost was not the limiting factor for proxy development. A good agreement with permafrost and climate proxy data is achieved when easterly winds are modelled more frequently.
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Panitz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev., 14, 5125–5154, https://doi.org/10.5194/gmd-14-5125-2021, https://doi.org/10.5194/gmd-14-5125-2021, 2021
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We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia, and Africa. How the model configuration, horizontal and vertical resolutions, and choice of driving data influence the model results for the five domains is assessed, with the purpose of aiding the planning and design of regional climate simulations in the future.
Patricio Velasquez, Jed O. Kaplan, Martina Messmer, Patrick Ludwig, and Christoph C. Raible
Clim. Past, 17, 1161–1180, https://doi.org/10.5194/cp-17-1161-2021, https://doi.org/10.5194/cp-17-1161-2021, 2021
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This study assesses the importance of resolution and land–atmosphere feedbacks for European climate. We performed an asynchronously coupled experiment that combined a global climate model (~ 100 km), a regional climate model (18 km), and a dynamic vegetation model (18 km). Modelled climate and land cover agree reasonably well with independent reconstructions based on pollen and other paleoenvironmental proxies. The regional climate is significantly influenced by land cover.
Assaf Hochman, Sebastian Scher, Julian Quinting, Joaquim G. Pinto, and Gabriele Messori
Earth Syst. Dynam., 12, 133–149, https://doi.org/10.5194/esd-12-133-2021, https://doi.org/10.5194/esd-12-133-2021, 2021
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Skillful forecasts of extreme weather events have a major socioeconomic relevance. Here, we compare two approaches to diagnose the predictability of eastern Mediterranean heat waves: one based on recent developments in dynamical systems theory and one leveraging numerical ensemble weather forecasts. We conclude that the former can be a useful and cost-efficient complement to conventional numerical forecasts for understanding the dynamics of eastern Mediterranean heat waves.
Cited articles
Alfieri, L., Dottori, F., Betts, R., Salamon, P., and Feyen, L.: Multi-model
projections of river flood risk in Europe under global warming, Climate, 6, 1–19, https://doi.org/10.3390/cli6010006, 2018. a
Arheimer, B., Lindström, G., and Olsson, J.: A systematic review of
sensitivities in the Swedish flood-forecasting system, Atmos. Res., 100,
275–284, https://doi.org/10.1016/j.atmosres.2010.09.013, 2011. a
Beck, H. E., Bruijnzeel, L. A., van Dijk, A. I. J. M., McVicar, T. R., Scatena, F. N., and Schellekens, J.: The impact of forest regeneration on streamflow in 12 mesoscale humid tropical catchments, Hydrol. Earth Syst. Sci., 17, 2613–2635, https://doi.org/10.5194/hess-17-2613-2013, 2013. a
Beck, H. E., van Dijk, A. I., De Roo, A., Miralles, D. G., McVicar, T. R.,
Schellekens, J., and Bruijnzeel, L. A.: Global-scale regionalization of
hydrologic model parameters, Water Resour. Res., 52, 3599–3622,
https://doi.org/10.1002/2015WR018247, 2016. a
Berg, P., Feldmann, H., and Panitz, H.-J.: Bias correction of high resolution
regional climate model data, J. Hydrol., 448, 80–92,
https://doi.org/10.1016/j.jhydrol.2012.04.026, 2012. a, b, c
Bergström, S. and Forsman, A.: Development of a conceptual deterministic
rainfall-runoff mode, Nord. Hydrol., 4, 240–253, 1973. a
Bosshard, T., Kotlarski, S., Zappa, M., and Schär, C.: Hydrological
climate-impact projections for the Rhine River: GCM–RCM uncertainty and
separate temperature and precipitation effects, J. Hydrometeorol., 15,
697–713, https://doi.org/10.1175/JHM-D-12-098.1, 2014. a
Cannon, A. J.: Reductions in daily continental-scale atmospheric circulation
biases between generations of global climate models: CMIP5 to CMIP6, Environ.
Res. Lett., 15, 064006, https://doi.org/10.1088/1748-9326/ab7e4f, 2020. a
Chen, J., Brissette, F. P., and Lucas-Picher, P.: Assessing the limits of
bias-correcting climate model outputs for climate change impact studies, J.
Geophys. Res.-Atmos., 120, 1123–1136, https://doi.org/10.1002/2014JD022635, 2015. a
Chen, J., Brissette, F. P., and Chen, H.: Using reanalysis-driven regional
climate model outputs for hydrology modelling, Hydrol. Process., 32,
3019–3031, https://doi.org/10.1002/hyp.13251, 2018. a, b
Chen, J., Brissette, F. P., Zhang, X. J., Chen, H., Guo, S., and Zhao, Y.: Bias
correcting climate model multi-member ensembles to assess climate change
impacts on hydrology, Climatic Change, 153, 361–377,
https://doi.org/10.1007/s10584-019-02393-x, 2019. a, b
Cloke, H. L., Wetterhall, F., He, Y., Freer, J. E., and Pappenberger, F.:
Modelling climate impact on floods with ensemble climate projections, Q. J.
Roy. Meteor. Soc., 139, 282–297, https://doi.org/10.1002/qj.1998, 2013. a, b
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J.,
Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P.,
Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman,
P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri,
M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L.,
Woodruff, S. D., and Worley, S. J.: The Twentieth Century Reanalysis Project,
Q. J. Roy. Meteor. Soc., 137, 1–28, https://doi.org/10.1002/qj.776, 2011. a
Coppola, E., Sobolowski, S., Pichelli, E., Raffaele, F., Ahrens, B., Anders,
I., Ban, N., Bastin, S., Belda, M., Belusic, D., Caldas-Alvarez, A., Cardoso,
R. M., Davolio, S., Dobler, A., Fernandez, J., Fita, L., Fumiere, Q., Giorgi,
F., Goergen, K., Güttler, I., Halenka, T., Heinzeller, D., Hodnebrog,
Ø., Jacob, D., Kartsios, S., Katragkou, E., Kendon, E., Khodayar, S.,
Kunstmann, H., Knist, S.and Lavin-Gullon, A., Lind, P., Lorenz, T., Maraun,
D., Marelle, L., van Meijgaard, E., Milovac, J., Myhre, G., Panitz, H.-J.,
Piazza, M., Raffa, M., Raub, T., Rockel, B., Schär, C., Sieck, K.,
Soares, P. M. M., Somot, S., Srnec, L., Stocchi, P., Tölle, M. H.,
Truhetz, H., Vautard, R., de Vries, H., and Warrach-Sagi, K.: A
first-of-its-kind multi-model convection permitting ensemble for
investigating convective phenomena over Europe and the Mediterranean, Clim.
Dynam., 55, 3–34, https://doi.org/10.1007/s00382-018-4521-8, 2020. a
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J., and Jones, P. D.:
An Ensemble Version of the E-OBS Temperature and Precipitation
Data Sets, J. Geophys. Res.-Atmos., 123, 9391–9409,
https://doi.org/10.1029/2017JD028200, 2018. a
Cunge, J.: On the subject of a flood propagation computation method (Musklngum
method), J. Hydrol. Res., 7, 205–230, https://doi.org/10.1080/00221686909500264, 1969. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and
Vitart, F.: The
ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011. a
Demirel, M. C., Booij, M. J., and Hoekstra, A. Y.: The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models, Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015, 2015. a
Dobler, A. and Ahrens, B.: Precipitation by a regional climate model and bias
correction in Europe and South Asia, Meteorol. Z., 17, 499–509,
https://doi.org/10.1127/0941-2948/2008/0306, 2008. a, b
ECA&D:
E-OBS gridded dataset, https://www.ecad.eu/download/ensembles/download.php, last access: 28 February 2022. a
Ehmele, F. and Kunz, M.: Flood-related extreme precipitation in southwestern Germany: development of a two-dimensional stochastic precipitation model, Hydrol. Earth Syst. Sci., 23, 1083–1102, https://doi.org/10.5194/hess-23-1083-2019, 2019. a
Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions ”Should we apply bias correction to global and regional climate model data?”, Hydrol. Earth Syst. Sci., 16, 3391–3404, https://doi.org/10.5194/hess-16-3391-2012, 2012. a, b, c
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Fang, G. H., Yang, J., Chen, Y. N., and Zammit, C.: Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China, Hydrol. Earth Syst. Sci., 19, 2547–2559, https://doi.org/10.5194/hess-19-2547-2015, 2015. a, b, c
Feldmann, H., Frueh, B., Schaedler, G., Panitz, H.-J., Keuler, K., Jacob, D.,
and Lorenz, P.: Evaluation of the precipitation for South-western Germany
from high resolution simulations with regional climate models, Meteorol. Z.,
17, 455–465, https://doi.org/10.1127/0941-2948/2008/0295, 2008. a
Feldmann, H., Schädler, G., Panitz, H.-J., and Kottmeier, C.: Near future
changes of extreme precipitation over complex terrain in Central Europe
derived from high resolution RCM ensemble simulations, Int. J. Climatol., 33,
1964–1977, https://doi.org/10.1002/joc.3564, 2013. a
Feldmann, H., Pinto, J. G., Laube, N., Uhlig, M., Moemken, J., Pasternack, A.,
Früh, B., Pohlmann, H., and Kottmeier, C.: Skill and added value of the
MiKlip regional decadal prediction system for temperature over Europe, Tellus
A, 71, 1618678, https://doi.org/10.1080/16000870.2019.1618678, 2019. a
Feser, F., Rockel, B., von Storch, H., Winterfeldt, J., and Zahn, M.: Regional
climate models add value to global model data: a review and selected
examples, B. Am. Meteorol. Soc., 92, 1181–1192,
https://doi.org/10.1175/2011BAMS3061.1, 2011. a
Feyen, L., Dankers, R., Bódis, K., Salamon, P., and Barredo, J. I.: Fluvial
flood risk in Europe in present and future climates, Climatic Change, 112,
47–62, https://doi.org/10.1007/s10584-011-0339-7, 2012. a, b
Frei, C., Davies, H. C., Gurtz, J., and Schär, C.: Climate dynamics and
extreme precipitation and flood events in Central Europe, Integrat.
Assess., 1, 281–300, https://doi.org/10.1023/A:1018983226334, 2000. a
Fuentes, U. and Heimann, D.: An improved statistical-dynamical downscaling
scheme and its application to the Alpine precipitation climatology, Theor.
Appl. Climatol., 65, 119–135, https://doi.org/10.1007/s007040070038, 2000. a
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J.,
Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K.,
Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L.,
Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan,
F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R.,
Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J.,
Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and Stevens, B.:
Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for
the Coupled Model Intercomparison Project phase 5, J. Adv.
Model. Earth Sy., 5, 572–597, https://doi.org/10.1002/jame.20038, 2013. a
Grams, C. M., Binder, H., Pfahl, S., Piaget, N., and Wernli, H.: Atmospheric processes triggering the central European floods in June 2013, Nat. Hazards Earth Syst. Sci., 14, 1691–1702, https://doi.org/10.5194/nhess-14-1691-2014, 2014. a
Gutjahr, O. and Heinemann, G.: Comparing precipitation bias correction methods
for high-resolution regional climate simulations using COSMO-CLM, Theor.
Appl. Climatol., 114, 511–529, https://doi.org/10.1007/s00704-013-0834-z, 2013. a
Gutmann, E. D., Rasmussen, R. M., Liu, C., Ikeda, K., Gochis, D. J., Clark,
M. P., Dudhia, J., and Thompson, G.: A comparison of statistical and
dynamical downscaling of winter precipitation over complex terrain, J.
Climate, 25, 262–281, https://doi.org/10.1175/2011JCLI4109.1, 2012. a
Haas, R., Pinto, J. G., and Born, K.: Can dynamically downscaled windstorm
footprints be improved by observations through a probabilistic approach?, J.
Geophys. Res.-Atmos., 119, 713–725, https://doi.org/10.1002/2013JD020882, 2014. a
Haylock, M., Hofstra, N., Tank, A. K., Klok, E., Jones, P., and New, M.: A
European daily high-resolution gridded data set of surface temperature and
precipitation for 1950–2006, J. Geophys. Res., 113, D20119,
https://doi.org/10.1029/2008JD010201, 2008. a, b, c, d
He, Y., Bárdossy, A., and Zehe, E.: A catchment classification scheme using
local variance reduction method, J. Hydrol., 411, 140–154,
https://doi.org/10.1016/j.jhydrol.2011.09.042, 2011. a, b
He, Y., Manful, D., Warren, R., Price, J., Forstenhäusler, N., Osborn, T.,
Wallace, C., and Yamazaki, D.: Quantification of impacts between 1.5 ∘C and 4 ∘C of
global warming on flooding risks in six countries, Climatic Change, 170, 1–21, https://doi.org/10.1007/s10584-021-03289-5,
2020. a
Hein, T., Funk, A., Pletterbauer, F., Graf, W., Zsuffa, I., Haidvogl, G.,
Schinegger, R., and Weigelhofer, G.: Management challenges related to
long-term ecological impacts, complex stressor interactions, and different
assessment approaches in the Danube River Basin, River Res. Appl., 35,
500–509, https://doi.org/10.1002/rra.3243, 2019. a
Hilker, N., Badoux, A., and Hegg, C.: The Swiss flood and landslide damage database 1972–2007, Nat. Hazards Earth Syst. Sci., 9, 913–925, https://doi.org/10.5194/nhess-9-913-2009, 2009. a
Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D.,
Watanabe, S., Kim, H., and Kanae, S.: Global flood risk under climate change,
Nat. Clim. Change, 3, 816, https://doi.org/10.1038/nclimate1911, 2013. a
Hosking, J. R. M.: L-Moments: Analysis and Estimation of Distributions Using
Linear Combinations of Order Statistics, J. Roy. Stat. Soc. B Met., 52,
105–124, https://doi.org/10.1111/j.2517-6161.1990.tb01775.x, 1990. a
Hunducha, Y. and Bardossy, A.: Modelling of the effect of land use changes on
the runoff generation of a river catchment through parameter regionalization
of a watershed model, J. Hydrol., 292, 281–295,
https://doi.org/10.1016/j.jhydrol.2004.01.002, 2004. a
Ionita, M.: Mid range forecasting of the German Waterways streamflow based
on hydrologic, atmospheric and oceanic data, Berichte zur Polar-und
Meeresforschung – Reports on polar and marine research, 711, 5–7, 2017. a
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.:
EURO-CORDEX: new high-resolution climate change projections for European
impact research, Reg. Environ. Change, 14, 563–578,
https://doi.org/10.1007/s10113-013-0499-2, 2014. a
Jenicek, M., Seibert, J., and Staudinger, M.: Modeling of future changes in
seasonal snowpack and impacts on summer low flows in alpine catchments, Water
Resour. Res., 54, 538–556, https://doi.org/10.1002/2017WR021648, 2018. a
Jongman, B., Hochrainer-Stigler, S., Feyen, L., Aerts, J. C., Mechler, R.,
Botzen, W. W., Bouwer, L. M., Pflug, G., Rojas, R., and Ward, P. J.:
Increasing stress on disaster-risk finance due to large floods, Nat. Clim.
Change, 4, 264, https://doi.org/10.1038/nclimate2124, 2014. a
Kelemen, F. D., Ludwig, P., Reyers, M., Ulbrich, S., and Pinto, J. G.:
Evaluation of moisture sources for the Central European summer flood of
May/June 2013 based on regional climate model simulations, Tellus, 68,
29288, https://doi.org/10.3402/tellusa.v68.29288, 2016. a
Krause, P., Boyle, D. P., and Bäse, F.: Comparison of different efficiency criteria for hydrological model assessment, Adv. Geosci., 5, 89–97, https://doi.org/10.5194/adgeo-5-89-2005, 2005. a
Kunz, M.: Characteristics of large-scale orographic precipitation in a linear
perspective, J. Hydrometeorol., 12, 27–44, https://doi.org/10.1175/2010JHM1231.1,
2011. a
Lang, M., Pobanz, K., Renard, B., Renouf, E., and Sauquet, E.: Extrapolation of
rating curves by hydraulic modelling, with application to flood frequency
analysis, Hydrolog. Sci. J., 55, 883–898,
https://doi.org/10.1080/02626667.2010.504186, 2010. a
Lidén, R. and Harlin, J.: Analysis of conceptual rainfall–runoff modelling
performance in different climates, J. Hydrol., 238, 231–247,
https://doi.org/10.1016/S0022-1694(00)00330-9, 2000. a
Lindström, G., Johansson, B., Persson, M., Gardelin, M., and Bergström,
S.: Development and test of the distributed HBV-96 hydrological model, J.
Hydrol., 201, 272–288, 1997. a
Maddox, R. A., Chappell, C. F., and Hoxit, L. R.: Synoptic and meso-α
scale aspects of flash flood events, B. Am. Meteorol. Soc., 60, 115–123,
1979. a
Makkonen, L.: Plotting Positions in Extreme Value Analysis, J. Appl. Meteorol.
Clim., 45, 334–340, https://doi.org/10.1175/JAM2349.1, 2006. a
Maraun, D.: Nonstationarities of regional climate model biases in European
seasonal mean temperature and precipitation sums, Geophys. Res. Lett., 39, L06706,
https://doi.org/10.1029/2012GL051210,, 2012. a
Maraun, D.: Bias correcting climate change simulations-a critical review, Curr.
Clim. Change Rep., 2, 211–220, https://doi.org/10.1007/s40641-016-0050-x, 2016. a
Marotzke, J., Müller, W. A., Vamborg, F. S. E., Becker, P., Cubasch, U., Feldmann, H., Kaspar, F., Kottmeier, C., Marini, C., Polkova, I., Prömmel, K., Rust, H. W., Stammer, D., Ulbrich, U., Kadow, C., Köhl, A., Kröger, J., Kruschke, T., Pinto, J. G., Pohlmann, H., Reyers, M., Schröder, M., Sienz, F., Timmreck, C., and Ziese, M.:
MiKlip: a national research project on decadal climate prediction, B. Am.
Meteorol. Soc., 97, 2379–2394, https://doi.org/10.1175/BAMS-D-15-00184.1, 2016. a
McCuen, R. H., Knight, Z., and Cutter, A. G.: Evaluation of the Nash-Sutcliffe
Efficiency Index, J. Hydrol. Eng., 11, 597–602,
https://doi.org/10.1061/(ASCE)1084-0699(2006)11:6(597), 2006. a
Merz, B., Elmer, F., Kunz, M., Mühr, B., Schröter, K., and
Uhlemann-Elmer, S.: The extreme flood in June 2013 in Germany, Houille
Blanche, 1, 5–10, https://doi.org/10.1051/lhb/2014001, 2014. a
Min, E., Hazeleger, W., Van Oldenborgh, G., and Sterl, A.: Evaluation of trends
in high temperature extremes in north-western Europe in regional climate
models, Environ. Res. Lett., 8, 014011,
https://doi.org/10.1088/1748-9326/8/1/014011, 2013. a
Müller, W. A., Matei, D., Bersch, M., Jungclaus, J. H., Haak, H., Lohmann,
K., Compo, G., Sardeshmukh, P., and Marotzke, J.: A twentieth-century
reanalysis forced ocean model to reconstruct the North Atlantic climate
variation during the 1920s, Clim. Dynam., 44, 1935–1955,
https://doi.org/10.1007/s00382-014-2267-5, 2015. a
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M.,
Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H., Ilyina, T., Kleine,
T., Kornblueh, L., Li, H., Modali, K., Notz, D., Pohlmann, H., Roeckner, E.,
Stemmler, I., Tian, F., and Marotzke, J.: A Higher-resolution Version of the
Max Planck Institute Earth System Model (MPI-ESM1.2-HR), J. Adv.
Model. Earth Sy., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018. a, b
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models,
Part I – A discussion of principles, J. Hydrol., 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970. a
Olsson, J. and Lindström, G.: Evaluation and calibration of operational
hydrological ensemble forecasts in Sweden, J. Hydrol., 350, 14–24,
https://doi.org/10.1016/j.jhydrol.2007.11.010, 2008. a
Ott, I., Duethmann, D., Liebert, J., Berg, P., Feldmann, H., Ihringer, J.,
Kunstmann, H., Merz, B., Schaedler, G., and Wagner, S.: High-resolution
climate change impact analysis on medium-sized river catchments in Germany:
an ensemble assessment, J. Hydrometeorol., 14, 1175–1193,
https://doi.org/10.1175/JHM-D-12-091.1, 2013. a
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil,
F., and Loumagne, C.: Which potential evapotranspiration input for a lumped
rainfall–runoff model?: Part 2 – Towards a simple and efficient
potential evapotranspiration model for rainfall–runoff modelling, J.
Hydrol., 303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026, 2005. a
Pauling, A. and Paeth, H.: On the variability of return periods of European winter precipitation extremes over the last three centuries, Clim. Past, 3, 65–76, https://doi.org/10.5194/cp-3-65-2007, 2007. a
Piani, C., Weedon, G., Best, M., Gomes, S., Viterbo, P., Hagemann, S., and
Haerter, J.: Statistical bias correction of global simulated daily
precipitation and temperature for the application of hydrological models, J.
Hydrol., 395, 199–215, https://doi.org/10.1016/j.jhydrol.2010.10.024, 2010. a, b
Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A., and Gratzki, A.: A
Central European precipitation climatology – Part I: Generation and validation
of a high-resolution gridded daily data set (HYRAS), Meteorol. Z., 22,
235–256, https://doi.org/10.1127/0941-2948/2013/0436, 2013. a, b
Raymond, C., Horton, R. M., Zscheischler, J., Martius, O., AghaKouchak, A., Balch, J., Bowen, S. G., Camargo, S. J., Hess, J., Kornhuber, K., Oppenheimer, M., Ruane, A. C., Wahl, T., and White, K.:
Understanding and managing connected extreme events, Nat. Clim. Change, 10,
611–621, https://doi.org/10.1038/s41558-020-0790-4, 2020. a
Reyers, M., Pinto, J. G., and Moemken, J.: Statistical–dynamical downscaling
for wind energy potentials: evaluation and applications to decadal hindcasts
and climate change projections, Int. J. Climatol., 35, 229–244,
https://doi.org/10.1002/joc.3975, 2015. a
Richardson, C. W.: Stochastic simulation of daily precipitation, temperature,
and solar radiation, Water Resour. Res., 17, 182–190,
https://doi.org/10.1029/WR017i001p00182, 1981. a
Rockel, B., Will, A., and Hense, A.: The regional climate model COSMO-CLM
(CCLM), Meteorol. Z., 17, 347–348, https://doi.org/10.1127/0941-2948/2008/0309,
2008. a
Schröter, K., Kunz, M., Elmer, F., Mühr, B., and Merz, B.: What made the June 2013 flood in Germany an exceptional event? A hydro-meteorological evaluation, Hydrol. Earth Syst. Sci., 19, 309–327, https://doi.org/10.5194/hess-19-309-2015, 2015. a
Seibert, S. P. and Auerswald, K.: Hochwasserminderung im ländlichen Raum:
Ein Handbuch zur quantitativen Planung, Springer Nature,
https://doi.org/10.1007/978-3-662-61033-6, 2020. a
Stucki, P., Dierer, S., Welker, C., Gómez-Navarro, J. J., Raible, C. C.,
Martius, O., and Brönnimann, S.: Evaluation of downscaled wind speeds and
parameterised gusts for recent and historical windstorms in Switzerland,
Tellus, 68, 31820, https://doi.org/10.3402/tellusa.v68.31820, 2016. a
Tapia, C., Guerreiro, S., Dawson, R., Abajo, B., Kilsby, C., Feliu, E.,
Mendizabal, M., Martinez, J., Fernández, J., Glenis, V., Eluwa, C.,
Laburu, T., and Lejarazu, A.: High level quantified assessment of key
vulnerabilities and priority risks for urban areas in the EU, RAMSES project
deliverable D, 3, https://climate-adapt.eea.europa.eu/metadata/publications/high-level-quantified-assessment-of-key-vulnerabilities-and-priority-risks-for-urban-areas-in-the-eu/ramses_2016_quantifiedassessmentkeyvulnerabilities.pdf
(last access: 2 March 2022),
2015. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the
experiment design, B. Am. Meteorol. Soc., 93, 485–498,
https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
Teng, J., Potter, N. J., Chiew, F. H. S., Zhang, L., Wang, B., Vaze, J., and Evans, J. P.: How does bias correction of regional climate model precipitation affect modelled runoff?, Hydrol. Earth Syst. Sci., 19, 711–728, https://doi.org/10.5194/hess-19-711-2015, 2015. a
Terink, W., Hurkmans, R. T. W. L., Torfs, P. J. J. F., and Uijlenhoet, R.: Evaluation of a bias correction method applied to downscaled precipitation and temperature reanalysis data for the Rhine basin, Hydrol. Earth Syst. Sci., 14, 687–703, https://doi.org/10.5194/hess-14-687-2010, 2010. a
Teutschbein, C. and Seibert, J.: Regional climate models for hydrological
impact studies at the catchment scale: a review of recent modeling
strategies, Geography Compass, 4, 834–860,
https://doi.org/10.1111/j.1749-8198.2010.00357.x, 2010. a
Teutschbein, C. and Seibert, J.: Bias correction of regional climate model
simulations for hydrological climate-change impact studies: Review and
evaluation of different methods, J. Hydrol., 456, 12–29,
https://doi.org/10.1016/j.jhydrol.2012.05.052, 2012. a
Tockner, K., Uehlinger, U., and Robinson, C. T.: Rivers of Europe, edited by: Tockner, K., Zarfl, C., and Robinson, C., Academic
Press, https://doi.org/10.1016/C2017-0-03745-X, 2009. a
Van den Besselaar, E., Haylock, M., Van der Schrier, G., and Klein Tank, A.: A
European daily high-resolution observational gridded data set of sea level
pressure, J. Geophys. Res., 116, D11110, https://doi.org/10.1029/2010JD015468, 2011. a
van Oldenborgh, G. J., Philip, S., Aalbers, E., Vautard, R., Otto, F., Haustein, K., Habets, F., Singh, R., and Cullen, H.: Rapid attribution of the May/June 2016 flood-inducing precipitation in France and Germany to climate change, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2016-308, 2016. a
van Pelt, S. C., Kabat, P., ter Maat, H. W., van den Hurk, B. J. J. M., and Weerts, A. H.: Discharge simulations performed with a hydrological model using bias corrected regional climate model input, Hydrol. Earth Syst. Sci., 13, 2387–2397, https://doi.org/10.5194/hess-13-2387-2009, 2009. a
Vetter, T., Huang, S., Aich, V., Yang, T., Wang, X., Krysanova, V., and Hattermann, F.: Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents, Earth Syst. Dynam., 6, 17–43, https://doi.org/10.5194/esd-6-17-2015, 2015. a
Volpi, E., Fiori, A., Grimaldi, S., Lombardo, F., and Koutsoyiannis, D.: Save
hydrological observations! Return period estimation without data decimation,
J. Hydrol., 571, 782–792, https://doi.org/10.1016/j.jhydrol.2019.02.017, 2019. a
Ward, P. J., de Moel, H., and Aerts, J. C. J. H.: How are flood risk estimates affected by the choice of return-periods?, Nat. Hazards Earth Syst. Sci., 11, 3181–3195, https://doi.org/10.5194/nhess-11-3181-2011, 2011. a
White, R. and Toumi, R.: The limitations of bias correcting regional climate
model inputs, Geophys. Res. Lett., 40, 2907–2912, https://doi.org/10.1002/grl.50612,
2013. a
Zscheischler, J., Westra, S., Van Den Hurk, B. J. J. M., Seneviratne, S. I., Ward, P. J., Pitman, A., AghaKouchak, A., Bresch, D. N., Leonard, M., Wahl, T., and Zhang, X.: Future climate risk from compound events, Nat. Clim. Change, 8,
469–477, https://doi.org/10.1038/s41558-018-0156-3, 2018. a
Short summary
For various applications, it is crucial to have profound knowledge of the frequency, severity, and risk of extreme flood events. Such events are characterized by very long return periods which observations can not cover. We use a large ensemble of regional climate model simulations as input for a hydrological model. Precipitation data were post-processed to reduce systematic errors. The representation of precipitation and discharge is improved, and estimates of long return periods become robust.
For various applications, it is crucial to have profound knowledge of the frequency, severity,...
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