Articles | Volume 19, issue 6
https://doi.org/10.5194/os-19-1753-2023
© 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/os-19-1753-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Dec 2023
Research article |
| 08 Dec 2023
| 08 Dec 2023
Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hindcast ensemble for the Baltic Sea
Marvin Lorenz
CORRESPONDING AUTHOR
Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany
Ulf Gräwe
Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany
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Cited articles
Andersson, H. C.: Influence of long-term regional and large-scale atmospheric circulation on the Baltic Sea level, Tellus A, 54, 76–88, https://doi.org/10.3402/tellusa.v54i1.12125, 2002. a
Andrée, E., Su, J., Dahl Larsen, M. A., Drews, M., Stendel, M., and Skovgaard Madsen, K.: The role of preconditioning for extreme storm surges in the western Baltic Sea, Nat. Hazards Earth Syst. Sci., 23, 1817–1834, https://doi.org/10.5194/nhess-23-1817-2023, 2023. a
Arns, A., Wahl, T., Haigh, I., Jensen, J., and Pattiaratchi, C.: Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practise, Coast. Eng., 81, 51–66, https://doi.org/10.1016/j.coastaleng.2013.07.003, 2013. a, b
Arns, A., Wahl, T., Wolff, C., Vafeidis, A. T., Haigh, I. D., Woodworth, P., Niehüser, S., and Jensen, J.: Non-linear interaction modulates global extreme sea levels, coastal flood exposure, and impacts, Nat. Commun., 11, 1–9, https://doi.org/10.1038/s41467-020-15752-5, 2020. a, b, c
Bamber, J. L., Oppenheimer, M., Kopp, R. E., Aspinall, W. P., and Cooke, R. M.: Ice sheet contributions to future sea-level rise from structured expert judgment, P. Natl. Acad. Sci. USA, 116, 11195–11200, https://doi.org/10.1073/pnas.1817205116, 2019. a
Barbosa, S. M.: Quantile trends in Baltic sea level, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008gl035182, 2008. a
Bierstedt, S. E., Hünicke, B., and Zorita, E.: Variability of wind direction statistics of mean and extreme wind events over the Baltic Sea region, Tellus A, 67, 29073, https://doi.org/10.3402/tellusa.v67.29073, 2015. a
Bork, I. and Müller-Navarra, S. H.: Modellierung von extremen Sturmhochwassern an der deutschen Ostseeküste, Die Küste, 75 MUSTOK, 71–130, 2009. a
Burchard, H. and Bolding, K.: GETM, A General Estuarine Transport Model: Scientific Documentation, Tech. Rep. EUR 20253, EN, Eur. Comm., 2002. a
Christensen, O. B., Kjellström, E., Dieterich, C., Gröger, M., and Meier, H. E. M.: Atmospheric regional climate projections for the Baltic Sea region until 2100, Earth Syst. Dynam., 13, 133–157, https://doi.org/10.5194/esd-13-133-2022, 2022. a
Coles, S., Bawa, J., Trenner, L., and Dorazio, P.: An introduction to statistical modeling of extreme values, Springer, ISBN 1-85233-459-2, https://doi.org/10.1007/978-1-4471-3675-0, 2001. a, b, c, d
Copernicus Climate Change Service: Climate Data Store: UERRA regional reanalysis for Europe on height levels from 1961 to 2019, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.44ec8078, 2019. a
Dieterich, C., Gröger, M., Arneborg, L., and Andersson, H. C.: Extreme sea levels in the Baltic Sea under climate change scenarios – Part 1: Model validation and sensitivity, Ocean Sci., 15, 1399–1418, https://doi.org/10.5194/os-15-1399-2019, 2019. a
Eelsalu, M., Soomere, T., Pindsoo, K., and Lagemaa, P.: Ensemble approach for projections of return periods of extreme water levels in Estonian waters, Cont. Shelf Res., 91, 201–210, https://doi.org/10.1016/j.csr.2014.09.012, 2014. a
Errico, R. M.: What is an adjoint model?, B. Am. Meteorol. Soc., 78, 2577–2592, https://doi.org/10.1175/1520-0477(1997)078<2577:wiaam>2.0.co;2, 1997. a
Feuchter, D., Jörg, C., Rosenhagen, G., Auchmann, R., Romppainen-Martius, O., and Brönnimann, S.: The 1872 Baltic Sea storm surge, Geograph. Bern., 89, 91–98, https://doi.org/10.4480/GB2013.G89.10, 2013. a
Fox-Kemper, B., Hewitt, H., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S., Edwards, T., Golledge, N., Hemer, M., Kopp, R., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I., Ruiz, L., Sallée, J.-B., Slangen, A., and Yu, Y.: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, https://doi.org/10.1017/9781009157896.011, 2021. 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, b
Geyer, B., Ludwig, T., and von Storch, H.: Limits of reproducibility and hydrodynamic noise in atmospheric regional modelling, Commun. Earth Environ., 2, 17, https://doi.org/10.1038/s43247-020-00085-4, 2021. a
Gräwe, U., Naumann, M., Mohrholz, V., and Burchard, H.: Anatomizing one of the largest saltwater inflows into the Baltic Sea in December 2014, J. Geophys. Res.-Oceans, 120, 7676–7697, https://doi.org/10.1002/2015JC011269, 2015. a
Gräwe, U., Klingbeil, K., Kelln, J., and Dangendorf, S.: Decomposing mean sea level rise in a semi-enclosed basin, the Baltic Sea, J. Climate, 32, 3089–3108, https://doi.org/10.1175/jcli-d-18-0174.1, 2019. a, b, c
Grinsted, A.: Projected Change – Sea Level, 253–263, Springer International Publishing, Cham, ISBN 978-3-319-16006-1, https://doi.org/10.1007/978-3-319-16006-1_14, 2015. a
Gröger, M., Placke, M., Meier, H. E. M., Börgel, F., Brunnabend, S.-E., Dutheil, C., Gräwe, U., Hieronymus, M., Neumann, T., Radtke, H., Schimanke, S., Su, J., and Väli, G.: The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment, Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, 2022. a
Haigh, I. D., Marcos, M., Talke, S. A., Woodworth, P. L., Hunter, J. R., Hague, B. S., Arns, A., Bradshaw, E., and Thompson, P.: GESLA Version 3: A major update to the global higher-frequency sea-level dataset, Geosci. Data J., https://doi.org/10.31223/x5mp65, 2022. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., et al.: 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
Hieronymus, M., Dieterich, C., Andersson, H., and Hordoir, R.: The effects of mean sea level rise and strengthened winds on extreme sea levels in the Baltic Sea, Theor. Appl., 8, 366–371, https://doi.org/10.1016/j.taml.2018.06.008, 2018. a
Hofstede, J. and Hamann, M.: The 1872 catastrophic storm surge at the Baltic Sea coast of Schleswig-Holstein; lessons learned?, Die Küste, https://doi.org/10.18171/1.092101, 2022. a
Hünicke, B. and Zorita, E.: Influence of temperature and precipitation on decadal Baltic Sea level variations in the 20th century, Tellus A, 58, 141–153, https://doi.org/10.1111/j.1600-0870.2006.00157.x, 2006. a
Kara, A. B., Rochford, P. A., and Hurlburt, H. E.: Efficient and accurate bulk parameterizations of air–sea fluxes for use in general circulation models, J. Atmos. Ocean. Tech., 17, 1421–1438, https://doi.org/10.1175/1520-0426(2000)017<1421:eaabpo>2.0.co;2, 2000. a, b, c, d
Karabil, S., Zorita, E., and Hünicke, B.: Contribution of atmospheric circulation to recent off-shore sea-level variations in the Baltic Sea and the North Sea, Earth Syst. Dynam., 9, 69–90, https://doi.org/10.5194/esd-9-69-2018, 2018. a
Kärnä, T., Ljungemyr, P., Falahat, S., Ringgaard, I., Axell, L., Korabel, V., Murawski, J., Maljutenko, I., Lindenthal, A., Jandt-Scheelke, S., Verjovkina, S., Lorkowski, I., Lagemaa, P., She, J., Tuomi, L., Nord, A., and Huess, V.: Nemo-Nordic 2.0: operational marine forecast model for the Baltic Sea, Geosci. Model Dev., 14, 5731–5749, https://doi.org/10.5194/gmd-14-5731-2021, 2021. a
Kärnä, T., Wallwork, J. G., and Kramer, S. C.: Efficient optimization of a regional water elevation model with an automatically generated adjoint, J. Adv. Model. Earth Syst., 15, e2022MS003169. https://doi.org/10.1029/2022MS003169, 2023. a
Kiesel, J., Lorenz, M., König, M., Gräwe, U., and Vafeidis, A. T.: Regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast, Nat. Hazards Earth Syst. Sci., 23, 2961–2985, https://doi.org/10.5194/nhess-23-2961-2023, 2023. a, b
Klingbeil, K., Lemarié, F., Debreu, L., and Burchard, H.: The numerics of hydrostatic structured-grid coastal ocean models: state of the art and future perspectives, Ocean Modell., 125, 80–105, https://doi.org/10.1016/j.ocemod.2018.01.007, 2018. a
Kudryavtseva, N., Pindsoo, K., and Soomere, T.: Non-stationary Modeling of Trends in Extreme Water Level Changes Along the Baltic Sea Coast, J. Coast. Res., 85, 586–590, https://doi.org/10.2112/SI85-118.1, 2018. a
Kudryavtseva, N., Soomere, T., and Männikus, R.: Non-stationary analysis of water level extremes in Latvian waters, Baltic Sea, during 1961–2018, Nat. Hazards Earth Syst. Sci., 21, 1279–1296, https://doi.org/10.5194/nhess-21-1279-2021, 2021. a, b, c
Large, W. and Yeager, S.: The global climatology of an interannually varying air–sea flux data set, Clim. Dynam., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2009. a
Lehmann, A., Getzlaff, K., and Harlaß, J.: Detailed assessment of climate variability in the Baltic Sea area for the period 1958 to 2009, Clim. Res., 46, 185–196, https://doi.org/10.3354/cr00876, 2011. a
Lorenz, M. and Gräwe, U.: Results of the study “Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hind-cast ensemble for the Baltic Sea” in Ocean Science (1.0) Zenodo [code, data set], https://doi.org/10.5281/zenodo.8340649, 2023a. a
Lorenz, M. and Gräwe, U.: Numerical hindcast ensemble for extreme sea levels in the Baltic Sea for 1979–2018, Leibniz Institute for Baltic Sea Research Warnemünde [data set], https://iowmeta.io-warnemuende.de/geonetwork/srv/eng/catalog.search#/metadata/IO W-IOWMETA-BalticSeaExtremeSeaLevelHindcastEnsemble-197 9-2018 (last access: 13 September 2023), 2023b. a
Madsen, K. S., Høyer, J. L., Fu, W., and Donlon, C.: Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the North Sea and Baltic Sea, J. Geophys. Res.-Oceans, 120, 6405–6418, https://doi.org/10.1002/2015JC011070, 2015. a
Männikus, R., Soomere, T., and Kudryavtseva, N.: Identification of mechanisms that drive water level extremes from in situ measurements in the Gulf of Riga during 1961-2017, Cont. Shelf Res., 182, 22–36, https://doi.org/10.1016/j.csr.2019.05.014, 2019. a
Männikus, R., Soomere, T., and Viška, M.: Variations in the mean, seasonal and extreme water level on the Latvian coast, the eastern Baltic Sea, during 1961–2018, Estuar. Coast. Shelf Sci., 245, 106827, https://doi.org/10.1016/j.ecss.2020.106827, 2020. a
Meier, H. E. M., Dieterich, C., Gröger, M., Dutheil, C., Börgel, F., Safonova, K., Christensen, O. B., and Kjellström, E.: Oceanographic regional climate projections for the Baltic Sea until 2100, Earth Syst. Dynam., 13, 159–199, https://doi.org/10.5194/esd-13-159-2022, 2022a. a, b
Meier, H. E. M., Kniebusch, M., Dieterich, C., Gröger, M., Zorita, E., Elmgren, R., Myrberg, K., Ahola, M. P., Bartosova, A., Bonsdorff, E., Börgel, F., Capell, R., Carlén, I., Carlund, T., Carstensen, J., Christensen, O. B., Dierschke, V., Frauen, C., Frederiksen, M., Gaget, E., Galatius, A., Haapala, J. J., Halkka, A., Hugelius, G., Hünicke, B., Jaagus, J., Jüssi, M., Käyhkö, J., Kirchner, N., Kjellström, E., Kulinski, K., Lehmann, A., Lindström, G., May, W., Miller, P. A., Mohrholz, V., Müller-Karulis, B., Pavón-Jordán, D., Quante, M., Reckermann, M., Rutgersson, A., Savchuk, O. P., Stendel, M., Tuomi, L., Viitasalo, M., Weisse, R., and Zhang, W.: Climate change in the Baltic Sea region: a summary, Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, 2022b. a, b
Meier, H. M., Broman, B., and Kjellström, E.: Simulated sea level in past and future climates of the Baltic Sea, Clim. Res., 27, 59–75, https://doi.org/10.3354/cr027059, 2004. a
Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C., and Ward, P. J.: A global reanalysis of storm surges and extreme sea levels, Nat. Commun., 7, 1–12, https://doi.org/10.1038/ncomms11969, 2016. a
Muis, S., Aerts, J., Antolínez, J. A. Á., Dullaart, J., Duong, T. M., Erikson, L., Haarmsa, R., Apecechea, M. I., Mengel, M., Le Bars, D., et al.: Global projections of storm surges using high-resolution CMIP6 climate models: validation, projected changes, and methodological challenges, Authorea Preprints, https://doi.org/10.1002/essoar.10511919.1, 2022. a
Peltier, W. R.: Global glacial isostasy and the surface of the ice-age Earth: the ICE-5G (VM2) model and GRACE, Annu. Rev. Earth Pl. Sc., 32, 111–149, https://doi.org/10.1146/annurev.earth.32.082503.144359, 2004. a
Peng, S., Li, Y., and Xie, L.: Adjusting the wind stress drag coefficient in storm surge forecasting using an adjoint technique, J. Atmos. Ocean. Technol., 30, 590–608, https://doi.org/10.1175/jtech-d-12-00034.1, 2013. a
Pietrzak, J.: The use of TVD limiters for forward-in-time upstream-biased advection schemes in ocean modeling, Mon. Weather Rev., 126, 812–830, https://doi.org/10.1175/1520-0493(1998)126<0812:tuotlf>2.0.co;2, 1998. a
Reinert, M., Pineau-Guillou, L., Raillard, N., and Chapron, B.: Seasonal shift in storm surges at Brest revealed by extreme value analysis, J. Geophys. Res.-Oceans, 126, e2021JC017794, https://doi.org/10.1029/2021jc017794, 2021. a
Rosenhagen, G. and Bork, I.: Rekonstruktion der Sturmwetterlage vom 13. November 1872, Die Küste, 75 MUSTOK, 51–70, 2009. a
Rutgersson, A., Kjellström, E., Haapala, J., Stendel, M., Danilovich, I., Drews, M., Jylhä, K., Kujala, P., Larsén, X. G., Halsnæs, K., Lehtonen, I., Luomaranta, A., Nilsson, E., Olsson, T., Särkkä, J., Tuomi, L., and Wasmund, N.: Natural hazards and extreme events in the Baltic Sea region, Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, 2022. a
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., et al.: The NCEP climate forecast system reanalysis, B. Am. Meteorol. Soc., 91, 1015–1058, https://doi.org/10.1175/2010bams3001.1, 2010. a
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H.-y., Iredell, M., et al.: The NCEP climate forecast system version 2, J. Climate, 27, 2185–2208, https://doi.org/10.1175/jcli-d-12-00823.1, 2014. a
Smith, S. D., Anderson, R. J., Oost, W. A., Kraan, C., Maat, N., De Cosmo, J., Katsaros, K. B., Davidson, K. L., Bumke, K., Hasse, L., et al.: Sea surface wind stress and drag coefficients: The HEXOS results, Bound.-Lay. Meteorol., 60, 109–142, https://doi.org/10.1007/bf00122064, 1992. a
Soomere, T., Eelsalu, M., Kurkin, A., and Rybin, A.: Separation of the Baltic Sea water level into daily and multi-weekly components, Cont. Shelf Res., 103, 23–32, https://doi.org/10.1016/j.csr.2015.04.018, 2015. a
Suursaar, Ü. and Sooäär, J.: Decadal variations in mean and extreme sea level values along the Estonian coast of the Baltic Sea, Tellus A, 59, 249–260, https://doi.org/10.1111/j.1600-0870.2006.00220.x, 2007. a, b, c
Tadesse, M. G. and Wahl, T.: A database of global storm surge reconstructions, Sci. Data, 8, 1–10, https://doi.org/10.1038/s41597-021-00906-x, 2021. a
Tadesse, M. G., Wahl, T., Rashid, M. M., Dangendorf, S., Rodríguez-Enríquez, A., and Talke, S. A.: Long-term trends in storm surge climate derived from an ensemble of global surge reconstructions, Sci. Rep., 12, 1–18, https://doi.org/10.1002/essoar.10511038.1, 2022. a
Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M., and DiMarco, S. F.: True colors of oceanography: Guidelines for effective and accurate colormap selection, Oceanography, 29, 9–13, https://doi.org/10.5670/oceanog.2016.66, 2016. a
Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Verlaan, M., and Feyen, L.: Extreme sea levels on the rise along Europe's coasts, Earth's Future, 5, 304–323, https://doi.org/10.1002/2016ef000505, 2017. a
Wahl, T., Haigh, I. D., Nicholls, R. J., Arns, A., Dangendorf, S., Hinkel, J., and Slangen, A. B.: Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis, Nat. Commun., 8, 1–12, https://doi.org/10.1038/ncomms16075, 2017. a
Weisse, R. and Weidemann, H.: Baltic Sea extreme sea levels 1948-2011: Contributions from atmospheric forcing, Procedia IUTAM, 25, 65–69, https://doi.org/10.1016/j.piutam.2017.09.010, 2017. a
Weisse, R., Dailidienė, I., Hünicke, B., Kahma, K., Madsen, K., Omstedt, A., Parnell, K., Schöne, T., Soomere, T., Zhang, W., and Zorita, E.: Sea level dynamics and coastal erosion in the Baltic Sea region, Earth Syst. Dynam., 12, 871–898, https://doi.org/10.5194/esd-12-871-2021, 2021. a, b, c
Wolski, T. and Wiśniewski, B.: Characteristics and Long-Term Variability of Occurrences of Storm Surges in the Baltic Sea, Atmosphere, 12, 1679, https://doi.org/10.3390/atmos12121679, 2021. a
Wolski, T. and Wiśniewski, B.: Characteristics of seasonal changes of the Baltic Sea extreme sea levels, Oceanologia, 65, 151–170, https://doi.org/10.1016/j.oceano.2022.02.006, 2023. a
Wolski, T., Wiśniewski, B., Giza, A., Kowalewska-Kalkowska, H., Boman, H., Grabbi-Kaiv, S., Hammarklint, T., Holfort, J., and Lydeikaitė, Ž.: Extreme sea levels at selected stations on the Baltic Sea coast, Oceanologia, 56, 259–290, https://doi.org/10.5697/oc.56-2.259, 2014. a
Woodworth, P. L., Hunter, J. R., Marcos, M., Caldwell, P., Menéndez, M., and Haigh, I.: Towards a global higher-frequency sea level dataset, Geosci. Data J., 3, 50–59, https://doi.org/10.1002/gdj3.42, 2016. a
Short summary
We study the variability of extreme sea levels in a 13 member hindcast ensemble for the Baltic Sea. The ensemble mean shows good agreement with observations regarding return levels and trends. However, we find great variability and uncertainty within the ensemble. We argue that the variability of storms in the atmospheric data directly translates into the variability of the return levels. These results highlight the need for large regional ensembles to minimise uncertainties.
We study the variability of extreme sea levels in a 13 member hindcast ensemble for the Baltic...
