Articles | Volume 23, issue 5
https://doi.org/10.5194/nhess-23-1967-2023
© Author(s) 2023. 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-23-1967-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 May 2023
Research article |
| 31 May 2023
| 31 May 2023
Compound flood events: analysing the joint occurrence of extreme river discharge events and storm surges in northern and central Europe
Philipp Heinrich
CORRESPONDING AUTHOR
Regional Land and Atmosphere Modeling, Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
Stefan Hagemann
Regional Land and Atmosphere Modeling, Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
Ralf Weisse
Coastal Climate and Regional Sea Level Changes, Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
Corinna Schrum
Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
Institute of Oceanography, University of Hamburg, Bundesstraße 53, 20146 Hamburg, Germany
Ute Daewel
Matter Transport and Ecosystem Dynamics, Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
Lidia Gaslikova
Coastal Climate and Regional Sea Level Changes, Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
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Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
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Xin Liu, Insa Meinke, and Ralf Weisse
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Tobias Stacke and Stefan Hagemann
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Matthias Gröger, Christian Dieterich, Jari Haapala, Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Jaromir Jakacki, Wilhelm May, H. E. Markus Meier, Paul A. Miller, Anna Rutgersson, and Lichuan Wu
Earth Syst. Dynam., 12, 939–973, https://doi.org/10.5194/esd-12-939-2021, https://doi.org/10.5194/esd-12-939-2021, 2021
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Regional climate studies are typically pursued by single Earth system component models (e.g., ocean models and atmosphere models). These models are driven by prescribed data which hamper the simulation of feedbacks between Earth system components. To overcome this, models were developed that interactively couple model components and allow an adequate simulation of Earth system interactions important for climate. This article reviews recent developments of such models for the Baltic Sea region.
Ralf Weisse, Inga Dailidienė, Birgit Hünicke, Kimmo Kahma, Kristine Madsen, Anders Omstedt, Kevin Parnell, Tilo Schöne, Tarmo Soomere, Wenyan Zhang, and Eduardo Zorita
Earth Syst. Dynam., 12, 871–898, https://doi.org/10.5194/esd-12-871-2021, https://doi.org/10.5194/esd-12-871-2021, 2021
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The study is part of the thematic Baltic Earth Assessment Reports – a series of review papers summarizing the knowledge around major Baltic Earth science topics. It concentrates on sea level dynamics and coastal erosion (its variability and change). Many of the driving processes are relevant in the Baltic Sea. Contributions vary over short distances and across timescales. Progress and research gaps are described in both understanding details in the region and in extending general concepts.
Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56, Fao, Rome, 300, D05109, ISBN 92-5-104219-5, 1998. a
Bermúdez, M., Farfán, J., Willems, P., and Cea, L.: Assessing the effects of climate change on compound flooding in coastal river areas, Water
Resour. Res., 57, e2020WR029321, https://doi.org/10.1029/2020WR029321, 2021. a
Bevacqua, E., Maraun, D., Vousdoukas, M. I., Voukouvalas, E., Vrac, M., Mentaschi, L., and Widmann, M.: Higher probability of compound flooding from
precipitation and storm surge in Europe under anthropogenic climate change,
Science Advances, 5, eaaw5531, https://doi.org/10.1126/sciadv.aaw5531, 2019. a, b, c, d
Bevacqua, E., Vousdoukas, M. I., Zappa, G., Hodges, K., Shepherd, T. G.,
Maraun, D., Mentaschi, L., and Feyen, L.: More meteorological events that
drive compound coastal flooding are projected under climate change,
Communications Earth & Environment, 1, 1–11,
https://doi.org/10.1038/s43247-020-00044-z, 2020. a
Bilskie, M. and Hagen, S.: Defining flood zone transitions in low-gradient
coastal regions, Geophys. Res. Lett., 45, 2761–2770,
https://doi.org/10.1002/2018GL077524, 2018. a
Bollmeyer, C., Keller, J.D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs, P., Hense, A., Keune, J., Kneifel, S., Pscheidt, I., Redl, S., and Steinke, S.: Towards a high-resolution regional reanalysis for the European CORDEX domain, Q. J. Roy. Meteor. Soc., 141, 1–15, https://doi.org/10.1002/qj.2486, 2015. a
Bundesamt für Seeschifffahrt und Hydrographie: Report on the oceanographic conditions at site N-7.2, https://pinta.bsh.de/N-7.2?tab=daten/N-07-02_oceanography_report_EN.pdf (last access: 19 April 2022), 2022. a
Camus, P., Haigh, I. D., Nasr, A. A., Wahl, T., Darby, S. E., and Nicholls, R. J.: Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns, Nat. Hazards Earth Syst. Sci., 21, 2021–2040, https://doi.org/10.5194/nhess-21-2021-2021, 2021. a, b
Chen, W.-B. and Liu, W.-C.: Modeling flood inundation induced by river flow and storm surges over a river basin, Water, 6, 3182–3199,
https://doi.org/10.3390/w6103182, 2014. 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
Couasnon, A., Eilander, D., Muis, S., Veldkamp, T. I. E., Haigh, I. D., Wahl, T., Winsemius, H. C., and Ward, P. J.: Measuring compound flood potential from river discharge and storm surge extremes at the global scale, Nat. Hazards Earth Syst. Sci., 20, 489–504, https://doi.org/10.5194/nhess-20-489-2020, 2020. a
Daewel, U. and Schrum, C.: Simulating long-term dynamics of the coupled North Sea and Baltic Sea ecosystem with ECOSMO II: Model description and validation, J. Marine Syst., 119, 30–49, https://doi.org/10.1016/j.jmarsys.2013.03.008, 2013. a
Davenport, F. V., Burke, M., and Diffenbaugh, N. S.: Contribution of historical precipitation change to US flood damages, P. Natl. Acad. Sci. USA, 118, e2017524118, https://doi.org/10.1073/pnas.2017524118, 2021. a
de Ruiter, M. C., Couasnon, A., van den Homberg, M. J., Daniell, J. E., Gill,
J. C., and Ward, P. J.: Why we can no longer ignore consecutive disasters,
Earths Future, 8, e2019EF001425, https://doi.org/10.1029/2019EF001425, 2020. a
Dietz, M.: Veränderungen der Großwetterlagen Mitteleuropas und ihr Einfluss
auf die Hochwassergefahr an großen Flüssen in Deutschland, Master's thesis,
Albert-Ludwigs-Universität Freiburg, http://www.hydrology.uni-freiburg.de/abschluss/Dietz_M_2019_MA.pdf (last access: 26 May 2023), 2019. a
DWD: Großwetterlagenklassifikation, DWD, Vorhersage- und Beratungszentrale [data set], https://www.dwd.de/DE/leistungen/grosswetterlage/grosswetterlage.html, last access: 26 May 2023. a
Engeland, K., Hisdal, H., and Frigessi, A.: Practical extreme value modelling
of hydrological floods and droughts: a case study, Extremes, 7, 5–30,
https://doi.org/10.1007/s10687-004-4727-5, 2004. a
European Commission and Directorate-General for European Civil Protection and Humanitarian Aid Operations (ECHO): Overview of natural and man-made
disaster risks the European Union may face: 2020 edition, Publications
Office, https://doi.org/10.2795/19072, 2021. a
Fang, J., Wahl, T., Fang, J., Sun, X., Kong, F., and Liu, M.: Compound flood potential from storm surge and heavy precipitation in coastal China: dependence, drivers, and impacts, Hydrol. Earth Syst. Sci., 25, 4403–4416, https://doi.org/10.5194/hess-25-4403-2021, 2021. a
Feser, F., Barcikowska, M., Krueger, O., Schenk, F., Weisse, R., and Xia, L.:
Storminess over the North Atlantic and northwestern Europe – A review,
Q. J. Roy. Meteor. Soc., 141, 350–382, https://doi.org/10.1002/qj.2364, 2015. a
Feyen, L., Ciscar, J.C., Gosling, S., Ibarreta, D., and Soria, A.: Climate change impacts and adaptation in Europe. JRC PESETA IV
final report, Tech. rep., Joint Research Centre (Seville site),
https://doi.org/10.2760/171121, 2020. a
Ganguli, P. and Merz, B.: Trends in compound flooding in northwestern Europe
during 1901–2014, Geophys. Res. Lett., 46, 10810–10820,
https://doi.org/10.1029/2019GL084220, 2019. a
Ganguli, P., Paprotny, D., Hasan, M., Güntner, A., and Merz, B.: Projected changes in compound flood hazard from riverine and coastal floods in northwestern Europe, Earths Future, 8, e2020EF001752,
https://doi.org/10.1029/2020EF001752, 2020. a, b, c, d
Gerstengarbe, F.-W., Werner, P. C., and Rüge, U.: Katalog der
Grosswetterlagen Europas (1881–1998) nach Paul Hess und Helmuth Brezowsky,
Potsdam-Institut für Klimafolgenforschung, https://www.pik-potsdam.de/en/output/publications/pikreports/.files/pr119.pdf (last access: 26 May 2023), 1999. a
Geyer, B.: High-resolution atmospheric reconstruction for Europe 1948–2012: coastDat2, Earth Syst. Sci. Data, 6, 147–164, https://doi.org/10.5194/essd-6-147-2014, 2014. a
Grabau, J.: Klimaschwankungen und Grosswetterlagen in Mitteleuropa seit 1881, Geogr. Helv., 42, 35–40, https://doi.org/10.5194/gh-42-35-1987, 1987. a
Gumbel, E. J.: Statistics of extremes, Columbia university press, https://doi.org/10.7312/gumb92958, 1958. a
Hagemann, S. and Ho-Hagemann, H. T.: The Hydrological Discharge Model – a river runoff component for offline and coupled model applications, Zenodo [code], https://doi.org/10.5281/zenodo.4893099, 2021. a
Hagemann, S. and Stacke, T.: Forcing for HD Model from HydroPy and subsequent HD Model river runoff over Europe based on EOBS22 and ERA5 data, World Data Center for Climate (WDCC) at DKRZ [data set], https://doi.org/10.26050/WDCC/EOBS_ERA5-River_Runoff, 2021. a, b
Hagemann, S. and Stacke, T.: Complementing ERA5 and E-OBS with high-resolution river discharge over Europe, Oceanologia, 65, 230–248, https://doi.org/10.1016/j.oceano.2022.07.003, 2022. a, b
Hagemann, S., Stacke, T., and Ho-Hagemann, H.: High resolution discharge
simulations over Europe and the Baltic Sea catchment, Front. Earth
Sci., 8, 12, https://doi.org/10.3389/feart.2020.00012, 2020. a
Haigh, I. D., Wadey, M. P., Wahl, T., Ozsoy, O., Nicholls, R. J., Brown, J. M., Horsburgh, K., and Gouldby, B.: Spatial and temporal analysis of extreme sea level and storm surge events around the coastline of the UK, Scientific Data, 3, 1–14, https://doi.org/10.1038/sdata.2016.107, 2016. a
Hao, Z., Singh, V. P., and Hao, F.: Compound extremes in hydroclimatology: a
review, Water, 10, 718, https://doi.org/10.3390/w10060718, 2018. a
Harley, M.: Coastal storm definition, Coastal Storms: Processes and Impacts,
edited by: Ciavola, P. and Coco, G., John Wiley and Sons, Chichester, UK, 1–21, https://doi.org/10.1002/9781118937099.ch1, 2017. a, b
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R.,
Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del
Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P.,
Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362,
https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Hendry, A., Haigh, I. D., Nicholls, R. J., Winter, H., Neal, R., Wahl, T., Joly-Laugel, A., and Darby, S. E.: Assessing the characteristics and drivers of compound flooding events around the UK coast, Hydrol. Earth Syst. Sci., 23, 3117–3139, https://doi.org/10.5194/hess-23-3117-2019, 2019. a, b, c
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023. a
Hess, P. and Brezowsky, H.: Katalog der Grosswetterlagen Europas, Dt.
Wetterdienst, ISSN 0072-4130, 1969. a
Hoy, A., Sepp, M., and Matschullat, J.: Atmospheric circulation variability in Europe and northern Asia (1901 to 2010), Theor. Appl. Climatol., 113, 105–126, https://doi.org/10.1007/s00704-012-0770-3, 2013. a
Jaagus, J., Briede, A., Rimkus, E., and Remm, K.: Precipitation pattern in the Baltic countries under the influence of large-scale atmospheric circulation and local landscape factors, Int. J. Climatol., 30, 705–720, https://doi.org/10.1002/joc.1929, 2010. a
James, P.: An objective classification method for Hess and Brezowsky
Grosswetterlagen over Europe, Theor. Appl. Climatol., 88, 17–42, https://doi.org/10.1007/s00704-006-0239-3, 2007. a
Jane, R., Wahl, T., Santos, V. M., Misra, S. K., and White, K. D.: Assessing the Potential for Compound Storm Surge and Extreme River Discharge Events at
the Catchment Scale with Statistical Models: Sensitivity Analysis and
Recommendations for Best Practice, J. Hydrol. Eng., 27,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0002154, 2022. a
Joe, H.: Dependence modeling with copulas, CRC press, ISBN 9781032477374, 2014. a
Juarez, B., Stockton, S. A., Serafin, K. A., and Valle-Levinson, A.: Compound flooding in a subtropical estuary caused by Hurricane Irma 2017, Geophys. Res. Lett., 49, e2022GL099360, https://doi.org/10.1029/2022GL099360, 2022. a
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Roy, J., and Joseph, D.: The NCEP/NCAR 40-year
reanalysis project, B. Am. Meteorol. Soc., 77, 437–472, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996. a
Kapitza, H.: MOPS – a morphodynamical prediction system on cluster computers, in: International Conference on High Performance Computing for Computational Science, Springer, 63–68, https://doi.org/10.1007/978-3-540-92859-1_8, 2008. a
Kew, S. F., Selten, F. M., Lenderink, G., and Hazeleger, W.: The simultaneous occurrence of surge and discharge extremes for the Rhine delta, Nat. Hazards Earth Syst. Sci., 13, 2017–2029, https://doi.org/10.5194/nhess-13-2017-2013, 2013. a
Khanal, S., Lutz, A. F., Immerzeel, W. W., Vries, H. D., Wanders, N., and Hurk, B. V. D.: The impact of meteorological and hydrological memory on compound peak flows in the Rhine river basin, Atmosphere, 10, 171,
https://doi.org/10.3390/atmos10040171, 2019. a
Klein Tank, A., Wijngaard, J., Können, G., Böhm, R., Demarée, G., Gocheva, A., Mileta, M., Pashiardis, S., Hejkrlik, L., Kern-Hansen, C., Heino, R., Bessemoulin, P., Müller-Westermeier, G., Tzanakou, M., Szalai, S., Pálsdóttir, T., Fitzgerald, D., Rubin, S., Capaldo, M., Maugeri, M., Leitass, A., Bukantis, A., Aberfeld, R., van Engelen, A. F. V., Forland, E., Mietus, M., Coelho, F., Mares, C., Razuvaev, V., Nieplova, E., Cegnar, T., Antonio López, J., Dahlström, B., Moberg, A., Kirchhofer, W., Ceylan, A., Pachaliuk, O., Alexander, L. V., and Petrovic, P.: Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment, Int. J. Climatol., 22, 1441–1453, https://doi.org/10.1002/joc.773, 2002. a
Klok, E. and Klein Tank, A.: Updated and extended European dataset of daily climate observations, Int. J. Climatol., 29, 1182–1191, https://doi.org/10.1002/joc.1779, 2009. a
Kumbier, K., Carvalho, R. C., Vafeidis, A. T., and Woodroffe, C. D.: Investigating compound flooding in an estuary using hydrodynamic modelling: a case study from the Shoalhaven River, Australia, Nat. Hazards Earth Syst. Sci., 18, 463–477, https://doi.org/10.5194/nhess-18-463-2018, 2018. a
Lai, Y., Li, J., Gu, X., Liu, C., and Chen, Y. D.: Global compound floods from precipitation and storm surge: hazards and the roles of cyclones, J. Climate, 34, 8319–8339, https://doi.org/10.1175/JCLI-D-21-0050.1, 2021. a
Leonard, M., Westra, S., Phatak, A., Lambert, M., van den Hurk, B., McInnes,
K., Risbey, J., Schuster, S., Jakob, D., and Stafford-Smith, M.: A compound
event framework for understanding extreme impacts, WIRES Climate Change, 5, 113–128, https://doi.org/10.1002/wcc.252, 2014. a
Lian, J. J., Xu, K., and Ma, C.: Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China, Hydrol. Earth Syst. Sci., 17, 679–689, https://doi.org/10.5194/hess-17-679-2013, 2013. a
Liang, B., Shao, Z., Li, H., Shao, M., and Lee, D.: An automated threshold selection method based on the characteristic of extrapolated significant wave heights, Coast. Eng., 144, 22–32, https://doi.org/10.1016/j.coastaleng.2018.12.001, 2019. a
Liu, X., Meinke, I., and Weisse, R.: Still normal? Near-real-time evaluation of storm surge events in the context of climate change, Nat. Hazards Earth Syst. Sci., 22, 97–116, https://doi.org/10.5194/nhess-22-97-2022, 2022. a
Lyard, F., Lefevre, F., Letellier, T., and Francis, O.: Modelling the global
ocean tides: modern insights from FES2004, Ocean Dynam., 56, 394–415,
https://doi.org/10.1007/s10236-006-0086-x, 2006. a
McGranahan, G., Balk, D., and Anderson, B.: The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones, Environ. Urban., 19, 17–37, https://doi.org/10.1177/0956247807076960, 2007. a
Moftakhari, H., Schubert, J. E., AghaKouchak, A., Matthew, R. A., and Sanders, B. F.: Linking statistical and hydrodynamic modeling for compound flood hazard assessment in tidal channels and estuaries, Adv. Water
Resour., 128, 28–38, https://doi.org/10.1016/j.advwatres.2019.04.009, 2019. a
Müller, M. and Sacco, D.: Coastlines in crisis: key risks from rising
oceans, CIO Special, Deutsche Bank Chief Investment Office, https://www.deutschewealth.com/dam/deutschewealth/cio-perspectives/cio-special-assets/coastlines-in-crisis/CIO-Special-Coastlines-in-crisis-key-risks-from-rising-oceans.pdf
(last access: 6 May 2023), 2021. a
Nasr, A. A., Wahl, T., Rashid, M. M., Camus, P., and Haigh, I. D.: Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline, Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, 2021. a
Paprotny, D., Morales-Nápoles, O., and Jonkman, S. N.: HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870, Earth Syst. Sci. Data, 10, 565–581, https://doi.org/10.5194/essd-10-565-2018, 2018a. a
Paprotny, D., Vousdoukas, M. I., Morales-Nápoles, O., Jonkman, S. N., and Feyen, L.: Compound flood potential in Europe, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2018-132, 2018b. a
Paprotny, D., Vousdoukas, M. I., Morales-Nápoles, O., Jonkman, S. N., and
Feyen, L.: Pan-European hydrodynamic models and their ability to identify
compound floods, Nat. Hazards, 101, 933–957, https://doi.org/10.1007/s11069-020-03902-3, 2020. a, b
Petrik, R. and Geyer, B.: coastDat3 COSMO-CLM MERRA2, World Data Center for Climate (WDCC) at DKRZ [data set],
https://doi.org/10.26050/WDCC/coastDat3_COSMO-CLM_MERRA2, 2021. a
Pickands III, J.: Statistical inference using extreme order statistics,
Ann. Stat., 3, 119–131, 1975. a
Poschlod, B., Zscheischler, J., Sillmann, J., Wood, R. R., and Ludwig, R.:
Climate change effects on hydrometeorological compound events over southern
Norway, Weather and Climate Extremes, 28, 100253,
https://doi.org/10.1016/j.wace.2020.100253, 2020. a, b
Rakovec, O. and Kumar, R.: Mesoscale Hydrologic Model based historical streamflow simulation over Europe at
Rantanen, M., Jylhä, K., Särkkä, J., Räihä, J., and Leijala, U.: Characteristics of joint heavy precipitation and high sea level events on the Finnish coast in 1961–2020, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2021-314, 2021. a
Ridder, N., de Vries, H., and Drijfhout, S.: The role of atmospheric rivers in compound events consisting of heavy precipitation and high storm surges along the Dutch coast, Nat. Hazards Earth Syst. Sci., 18, 3311–3326, https://doi.org/10.5194/nhess-18-3311-2018, 2018. a
Rivoire, P., Martius, O., and Naveau, P.: A comparison of moderate and extreme ERA-5 daily precipitation with two observational data sets, Earth Space Sci., 8, e2020EA001633, https://doi.org/10.1029/2020EA001633, 2021. a
Robins, P. E., Lewis, M. J., Elnahrawi, M., Lyddon, C., Dickson, N., and Coulthard, T. J.: Compound flooding: Dependence at sub-daily scales between extreme storm surge and fluvial flow, Frontiers in Built Environment, 7, p. 116, https://doi.org/10.3389/fbuil.2021.727294, 2021. 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
Santos, V. M., Casas-Prat, M., Poschlod, B., Ragno, E., van den Hurk, B., Hao, Z., Kalmár, T., Zhu, L., and Najafi, H.: Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands, Hydrol. Earth Syst. Sci., 25, 3595–3615, https://doi.org/10.5194/hess-25-3595-2021, 2021a. a
Santos, V. M., Wahl, T., Jane, R., Misra, S. K., and White, K. D.: Assessing compound flooding potential with multivariate statistical models in a complex
estuarine system under data constraints, J. Flood Risk Manage., 14, e12749, https://doi.org/10.1111/jfr3.12749, 2021b. a
Schrum, C. and Backhaus, J. O.: Sensitivity of atmosphere–ocean heat exchange and heat content in the North Sea and the Baltic Sea, Tellus A, 51, 526–549, https://doi.org/10.1034/j.1600-0870.1992.00006.x, 1999. a
Seneviratne, S., Nicholls, N., Easterling, D., Goodess, C., Kanae, S., Kossin, J., Luo, Y., Marengo, J., McInnes, K., Rahimi, M., Reichstein, M., Sorteberg, A., Vera, C., Zhang, X., Alexander, L. V., Allen, S., Benito, G., Cavazos, T., Clague, J., Conway, D., Della-Marta, P. M., Gerber, M., Gong, S., Goswami, B. N., Hemer, M., Huggel, C., van den Hurk, B., Kharin, V. V., Kitoh, A., Klein Tank, A. M. G., Li, G., Mason, S. J., McGuire, W., van Oldenborgh, G. J., Orlowsky, B., Smith, S., Thiaw, W., Velegrakis, A., Yiou, P., Zhang, T., Zhou, T., and Zwiers, F. W.: Changes in climate extremes and their impacts on the natural physical environment, Cambridge University Press, https://doi.org/10.7916/d8-6nbt-s431, 2012. a
Serinaldi, F.: An uncertain journey around the tails of multivariate
hydrological distributions, Water Resour. Res., 49, 6527–6547,
https://doi.org/10.1002/wrcr.20531, 2013. a
Solari, S., Egüen, M., Polo, M. J., and Losada, M. A.: Peaks Over Threshold (POT): A methodology for automatic threshold estimation using goodness of fit p-value, Water Resour. Res., 53, 2833–2849, 2017. a
Stacke, T. and Hagemann, S.: HydroPy (v1.0): a new global hydrology model written in Python, Geosci. Model Dev., 14, 7795–7816, https://doi.org/10.5194/gmd-14-7795-2021, 2021. a
Svensson, C. and Jones, D. A.: Dependence between extreme sea surge, river flow and precipitation in eastern Britain, Int. J. Climatol., 22, 1149–1168,
https://doi.org/10.1002/joc.794, 2002. a, b
Svensson, C. and Jones, D. A.: Dependence between sea surge, river flow and precipitation in south and west Britain, Hydrol. Earth Syst. Sci., 8, 973–992, https://doi.org/10.5194/hess-8-973-2004, 2004. a
Thornthwaite, C. W.: An approach toward a rational classification of climate,
Geogr. Rev., 38, 55–94, 1948. a
United Nations: Factsheet: People and Oceans, United Nations, https://www.un.org/sustainabledevelopment/wp-content/uploads/2017/05/Ocean-fact-sheet-package.pdf
(last access: 22 February 2022), 2017. a
van den Hurk, B., van Meijgaard, E., de Valk, P., van Heeringen, K.-J., and
Gooijer, J.: Analysis of a compounding surge and precipitation event in the
Netherlands, Environ. Res. Lett., 10, 035001,
https://doi.org/10.1088/1748-9326/10/3/035001, 2015. a, b
von Storch, H., Langenberg, H., and Feser, F.: A spectral nudging technique for dynamical downscaling purposes, Mon. Weather Rev., 128, 3664–3673,
https://doi.org/10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2, 2000. a
Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Bianchi, A., Dottori, F.,
and Feyen, L.: Climatic and socioeconomic controls of future coastal flood
risk in Europe, Nat. Clim. Change, 8, 776–780,
https://doi.org/10.1038/s41558-018-0260-4, 2018. a
Ward, P. J., Couasnon, A., Eilander, D., Haigh, I. D., Hendry, A., Muis, S.,
Veldkamp, T. I., Winsemius, H. C., and Wahl, T.: Dependence between high
sea-level and high river discharge increases flood hazard in global deltas
and estuaries, Environ. Res. Lett., 13, 084012,
https://doi.org/10.1088/1748-9326/aad400, 2018. a, b, c
Xu, H., Tian, Z., Sun, L., Ye, Q., Ragno, E., Bricker, J., Mao, G., Tan, J., Wang, J., Ke, Q., Wang, S., and Toumi, R.: Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai, Nat. Hazards Earth Syst. Sci., 22, 2347–2358, https://doi.org/10.5194/nhess-22-2347-2022, 2022. a
Zheng, F., Westra, S., and Sisson, S. A.: Quantifying the dependence between
extreme rainfall and storm surge in the coastal zone, J. Hydrol.,
505, 172–187, https://doi.org/10.1016/j.jhydrol.2013.09.054, 2013. a
Zheng, F., Westra, S., Leonard, M., and Sisson, S. A.: Modeling dependence
between extreme rainfall and storm surge to estimate coastal flooding risk,
Water Resour. Res., 50, 2050–2071, https://doi.org/10.1002/2013WR014616, 2014. 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
High seawater levels co-occurring with high river discharges have the potential to cause destructive flooding. For the past decades, the number of such compound events was larger than expected by pure chance for most of the west-facing coasts in Europe. Additionally rivers with smaller catchments showed higher numbers. In most cases, such events were associated with a large-scale weather pattern characterized by westerly winds and strong rainfall.
High seawater levels co-occurring with high river discharges have the potential to cause...
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