Articles | Volume 16, issue 2
https://doi.org/10.5194/essd-16-1121-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-1121-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Feb 2024
Data description paper |
| 27 Feb 2024
| 27 Feb 2024
Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution
Transformation Pathways, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Sanne Muis
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Deltares, Delft, the Netherlands
Sönke Dangendorf
Department of River-Coastal Science and Engineering, Tulane University, New Orleans, LA, USA
Thomas Wahl
Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, FL, USA
National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL, USA
Julius Oelsmann
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München, Arcisstraße 21, 80333 Munich, Germany
Stefanie Heinicke
Transformation Pathways, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Katja Frieler
Transformation Pathways, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Matthias Mengel
Transformation Pathways, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
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Víctor Malagón-Santos, Aimée B. A. Slangen, Tim H. J. Hermans, Sönke Dangendorf, Marta Marcos, and Nicola Maher
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Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
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Dominik Paprotny and Matthias Mengel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-194, https://doi.org/10.5194/gmd-2022-194, 2022
Preprint withdrawn
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Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
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Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Katherine L. Towey, James F. Booth, Alejandra Rodriguez Enriquez, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 22, 1287–1300, https://doi.org/10.5194/nhess-22-1287-2022, https://doi.org/10.5194/nhess-22-1287-2022, 2022
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Coastal flooding due to storm surge from tropical cyclones is a significant hazard. The influence of tropical cyclone characteristics, including its proximity, intensity, path angle, and speed, on the magnitude of storm surge is examined along the eastern United States. No individual characteristic was found to be strongly related to how much surge occurred at a site, though there is an increased likelihood of high surge occurring when tropical cyclones are both strong and close to a location.
Ahmed A. Nasr, Thomas Wahl, Md Mamunur Rashid, Paula Camus, and Ivan D. Haigh
Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, https://doi.org/10.5194/hess-25-6203-2021, 2021
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We analyse dependences between different flooding drivers around the USA coastline, where the Gulf of Mexico and the southeastern and southwestern coasts are regions of high dependence between flooding drivers. Dependence is higher during the tropical season in the Gulf and at some locations on the East Coast but higher during the extratropical season on the West Coast. The analysis gives new insights on locations, driver combinations, and the time of the year when compound flooding is likely.
Matthias Mengel, Simon Treu, Stefan Lange, and Katja Frieler
Geosci. Model Dev., 14, 5269–5284, https://doi.org/10.5194/gmd-14-5269-2021, https://doi.org/10.5194/gmd-14-5269-2021, 2021
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To identify the impacts of historical climate change it is necessary to separate the effect of the different impact drivers. To address this, one needs to compare historical impacts to a counterfactual world with impacts that would have been without climate change. We here present an approach that produces counterfactual climate data and can be used in climate impact models to simulate counterfactual impacts. We make these data available through the ISIMIP project.
Jiayi Fang, Thomas Wahl, Jian Fang, Xun Sun, Feng Kong, and Min Liu
Hydrol. Earth Syst. Sci., 25, 4403–4416, https://doi.org/10.5194/hess-25-4403-2021, https://doi.org/10.5194/hess-25-4403-2021, 2021
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A comprehensive assessment of compound flooding potential is missing for China. We investigate dependence, drivers, and impacts of storm surge and precipitation for coastal China. Strong dependence exists between driver combinations, with variations of seasons and thresholds. Sea level rise escalates compound flood potential. Meteorology patterns are pronounced for low and high compound flood potential. Joint impacts from surge and precipitation were much higher than from each individually.
Denise Dettmering, Felix L. Müller, Julius Oelsmann, Marcello Passaro, Christian Schwatke, Marco Restano, Jérôme Benveniste, and Florian Seitz
Earth Syst. Sci. Data, 13, 3733–3753, https://doi.org/10.5194/essd-13-3733-2021, https://doi.org/10.5194/essd-13-3733-2021, 2021
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In this study, a new gridded altimetry-based regional sea level dataset for the North Sea is presented, named North SEAL. It is based on long-term multi-mission cross-calibrated altimetry data consistently preprocessed with coastal dedicated algorithms. On a 6–8 km wide triangular mesh, North SEAL provides time series of monthly sea level anomalies as well as sea level trends and amplitudes of the mean annual sea level cycle for the period 1995–2019 for various applications.
Paula Camus, Ivan D. Haigh, Ahmed A. Nasr, Thomas Wahl, Stephen E. Darby, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2021–2040, https://doi.org/10.5194/nhess-21-2021-2021, https://doi.org/10.5194/nhess-21-2021-2021, 2021
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In coastal regions, floods can arise through concurrent drivers, such as precipitation, river discharge, storm surge, and waves, which exacerbate the impact. In this study, we identify hotspots of compound flooding along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea. This regional assessment can be considered a screening tool for coastal management that provides information about which areas are more predisposed to experience compound flooding.
Yasser Hamdi, Ivan D. Haigh, Sylvie Parey, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 21, 1461–1465, https://doi.org/10.5194/nhess-21-1461-2021, https://doi.org/10.5194/nhess-21-1461-2021, 2021
Julius Oelsmann, Marcello Passaro, Denise Dettmering, Christian Schwatke, Laura Sánchez, and Florian Seitz
Ocean Sci., 17, 35–57, https://doi.org/10.5194/os-17-35-2021, https://doi.org/10.5194/os-17-35-2021, 2021
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Vertical land motion (VLM) significantly contributes to relative sea level change. Here, we improve the accuracy and precision of VLM estimates, which are based on the difference of altimetry tide gauge observations. Advanced coastal altimetry and an improved coupling procedure of along-track altimetry data and high-frequency tide gauge observations are key factors for a greater comparability of altimetry and tide gauges in the coastal zone and thus for more reliable VLM estimates.
Robert Jane, Luis Cadavid, Jayantha Obeysekera, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 20, 2681–2699, https://doi.org/10.5194/nhess-20-2681-2020, https://doi.org/10.5194/nhess-20-2681-2020, 2020
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Full dependence is assumed between drivers in flood protection assessments of coastal water control structures in south Florida. A 2-D analysis of rainfall and coastal water level showed that the magnitude of the conservative assumption in the original design is highly sensitive to the regional sea level rise projection considered. The vine copula and HT04 model outperformed five higher-dimensional copulas in capturing the dependence between rainfall, coastal water level, and groundwater level.
Cited articles
Albert, S., Leon, J. X., Grinham, A. R., Church, J. A., Gibbes, B. R., and Woodroffe, C. D.: Interactions between sea-level rise and wave exposure on reef island dynamics in the Solomon Islands, Environ. Res. Lett., 11, 054011, https://doi.org/10.1088/1748-9326/11/5/054011, 2016.
Annunziato, A. and Probst, P.: Continuous Harmonics Analysis of Sea Level Measurements: Description of a new method to determine sea level measurement tidal component, EUR 28308 EN, Ispra (Italy), Publications Office of the European Union, JRC104684, 2016.
Brown, S., Nicholls, R. J., Goodwin, P., Haigh, I. D., Lincke, D., Vafeidis, A. T., and Hinkel, J.: Quantifying land and people exposed to sea-level rise with no mitigation and 1.5° C and 2.0° C rise in global temperatures to year 2300, Earths Future, 6, 583–600, 2018.
Caldwell, P. C., Merrifield, M. A., and Thompson, P. R.: Sea level measured by tide gauges from global oceans – the Joint Archive for Sea Level holdings (NCEI Accession 0019568), Version 5.5, NOAA National Centers for Environmental Information [data set], https://doi.org/10.7289/V5V40S7W, 2015.
Caron, L., Ivins, E. R., Larour, E., Adhikari, S., Nilsson, J., and Blewitt, G.: GIA Model Statistics for GRACE Hydrology, Cryosphere, and Ocean Science, Geophys. Res. Lett., 45, 2203–2212, https://doi.org/10.1002/2017GL076644, 2018.
Church, J. A. and White, N. J.: Sea-Level Rise from the Late 19th to the Early 21st Century, Surv. Geophys., 32, 585–602, 2011.
Church, J. A., White, N. J., Konikow, L. F., Domingues, C. M., Cogley, J. G., Rignot, E., Gregory, J. M., van den Broeke, M. R., Monaghan, A. J., and Velicogna, I.: Revisiting the Earth's sea-level and energy budgets from 1961 to 2008, Geophys. Res. Lett., 38, L18601, https://doi.org/10.1029/2011gl048794, 2011.
Dangendorf, S., Calafat, F. M., Arns, A., Wahl, T., Haigh, I. D., and Jensen, J.: Mean sea level variability in the North Sea: Processes and implications, J. Geophys. Res.-Oceans, 119, 6820–6841, https://doi.org/10.1002/2014JC009901, 2014.
Dangendorf, S., Marcos, M., Wöppelmann, G., Conrad, C. P., Frederikse, T., and Riva, R.: Reassessment of 20th century global mean sea level rise, P. Natl. Acad. Sci. USA, 114, 5946–5951, 2017.
Dangendorf, S., Hay, C., Calafat, F. M., Marcos, M., Piecuch, C. G., Berk, K., and Jensen, J.: Persistent acceleration in global sea-level rise since the 1960s, Nat. Clim. Change, 9, 705–710, 2019.
Dangendorf, S., Frederikse, T., Chafik, L., Klinck, J. M., Ezer, T., and Hamlington, B. D.: Data-driven reconstruction reveals large-scale ocean circulation control on coastal sea level, Nat. Clim. Change, 11, 514–520, 2021.
Dullaart, J. C. M., Muis, S., Bloemendaal, N., and Aerts, J. C. J. H.: Advancing global storm surge modelling using the new ERA5 climate reanalysis, Clim. Dynam., 54, 1007–1021, 2020.
Emery, K. O. and Aubrey, D. G.: Glacial rebound and relative sea levels in Europe from tide-gauge records, Tectonophysics, 120, 239–255, 1985.
Enríquez-de-Salamanca, Á.: Evolution of coastal erosion in Palmarin (Senegal), J. Coast. Conserv., 24, 25, 1874–7841, https://doi.org/10.1007/s11852-020-00742-y, 2020.
E.U. Copernicus Marine Service Information (CMEMS): Global Ocean Mean Dynamic Topography SEALEVEL_GLO_PHY_MDT_008_063, Marine Data Store (MDS) [data set], https://doi.org/10.48670/moi-00150, 2024.
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B., Slangen, A. B. A., and Yu, A. 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, edited by: MassonDelmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, 1211–1362, https://doi.org/10.1017/9781009157896.011, 2021.
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V. W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L., and Wu, Y.-H.: The causes of sea-level rise since 1900, Nature, 584, 393–397, 2020.
Gesch, D. B.: Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure, Front Earth Sci. Chin., 6, 230, https://doi.org/10.3389/feart.2018.00230, 2018.
Gillett, N. P., Shiogama, H., Funke, B., Hegerl, G., Knutti, R., Matthes, K., Santer, B. D., Stone, D., and Tebaldi, C.: The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6, Geosci. Model Dev., 9, 3685–3697, https://doi.org/10.5194/gmd-9-3685-2016, 2016.
Haigh, I., Marcos Moreno, M., Talke, S., Woodworth, P., Hunter, J., Hague, B., Arns, A., Bradshaw, E., and Thompson, P.: The Global Extreme Sea Level Analysis (GESLA) Version 3 dataset: Part 1, NERC EDS British Oceanographic Data Centre NOC [data set], https://doi.org/10.5285/d21a496a-a48e-1f21-e053-6c86abc08512, 2022a.
Haigh, I., Marcos Moreno, M., Talke, S., Woodworth, P., Hunter, J., Hague, B., Arns, A., Bradshaw, E., and Thompson, P.: The Global Extreme Sea Level Analysis (GESLA) Version 3 dataset: Part 2, NERC EDS British Oceanographic Data Centre NOC [data set], https://doi.org/10.5285/d21a496a-a48f-1f21-e053-6c86abc08512, 2022b.
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., 10, 293–314, 2023.
Hallegatte, S., Green, C., Nicholls, R. J., and Corfee-Morlot, J.: Future flood losses in major coastal cities, Nat. Clim. Change, 3, 802–806, https://doi.org/10.1038/nclimate1979, 2013.
Hammond, W. C., Blewitt, G., Kreemer, C., and Nerem, R. S.: GPS Imaging of Global Vertical Land Motion for Studies of Sea Level Rise, J. Geophys. Res.-Sol. Ea., 126, e2021JB022355, https://doi.org/10.1029/2021JB022355, 2021.
Hawkins, R., Bodin, T., Sambridge, M., Choblet, G., and Husson, L.: Trans-dimensional surface reconstruction with different classes of parameterization, Geochem. Geophy. Geosy., 20, 505–529, 2019a.
Hawkins, R., Husson, L., Choblet, G., Bodin, T., and Pfeffer, J.: Virtual tide gauges for predicting relative sea level rise, J. Geophys. Res.-Sol. Ea., 124, 13367–13391, 2019b.
Hay, C. C., Morrow, E., Kopp, R. E., and Mitrovica, J. X.: Probabilistic reanalysis of twentieth-century sea-level rise, Nature, 517, 481–484, https://doi.org/10.1038/nature14093, 2015.
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., 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., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020.
Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S. J., Marzeion, B., Fettweis, X., Ionescu, C., and Levermann, A.: Coastal flood damage and adaptation costs under 21st century sea-level rise, P. Natl. Acad. Sci. USA, 111, 3292–3297, 2014.
Holgate, S. J., Matthews, A., Woodworth, P. L., Rickards, L. J., Tamisiea, M. E., Bradshaw, E., Foden, P. R., Gordon, K. M., Jevrejeva, S., and Pugh, J.: New Data Systems and Products at the Permanent Service for Mean Sea Level, coas, 29, 493–504, https://doi.org/10.2112/JCOASTRES-D-12-00175.1, 2013.
Hooijer, A. and Vernimmen, R.: Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics, Nat. Commun., 12, 3592, https://doi.org/10.1038/s41467-021-23810-9, 2021.
Hope, P., Cramer, W., van Aalst, M., Flato, G., Frieler, K., Gillett, N., Huggel, C., Minx, J., Otto, F., Parmesan, C., Rogelj, J., Rojas, M., Seneviratne, S. I., Slangen, A., Stone, D., Terray, L., Vautard, R., and Zhang, X.: Cross-Working Group Box ATTRIBUTION, in: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H. O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., Cambridge University Press, Cambridge, UK and New York, USA, 121–196, https://doi.org/10.1017/9781009325844, 2022.
Hunter, J. R., Woodworth, P. L., Wahl, T., and Nicholls, R. J.: Using global tide gauge data to validate and improve the representation of extreme sea levels in flood impact studies, Global Planet. Change, 156, 34–45, 2017.
Irish, J. L., Sleath, A., Cialone, M. A., Knutson, T. R., and Jensen, R. E.: Simulations of Hurricane Katrina (2005) under sea level and climate conditions for 1900, Clim. Change, 122, 635–649, 2014.
Kanwal, S., Ding, X., Sajjad, M., and Abbas, S.: Three Decades of Coastal Changes in Sindh, Pakistan (1989–2018): A Geospatial Assessment, Remote Sensing, 12, 8, https://doi.org/10.3390/rs12010008, 2020.
Kernkamp, H. W. J., Van Dam, A., Stelling, G. S., and de Goede, E. D.: Efficient scheme for the shallow water equations on unstructured grids with application to the Continental Shelf, Ocean Dynam., 61, 1175–1188, 2011.
Kirezci, E., Young, I. R., Ranasinghe, R., Lincke, D., and Hinkel, J.: Global-scale analysis of socioeconomic impacts of coastal flooding over the 21st century, Front. Mar. Sci., 9, 1024111, https://doi.org/10.3389/fmars.2022.1024111, 2023.
Kopp, R. E., Horton, R. M., Little, C. M., Mitrovica, J. X., Oppenheimer, M., Rasmussen, D. J., Strauss, B. H., and Tebaldi, C.: Probabilistic 21st and 22nd century sea-level projections at a global network of tide-gauge sites, Earth's Future, 2, 383–406, https://doi.org/10.1002/2014ef000239, 2014.
Lin, N., Kopp, R. E., Horton, B. P., and Donnelly, J. P.: Hurricane Sandy's flood frequency increasing from year 1800 to 2100, P. Natl. Acad. Sci. USA, 113, 12071–12075, 2016.
Luijendijk, A., Hagenaars, G., Ranasinghe, R., Baart, F., Donchyts, G., and Aarninkhof, S.: The State of the World's Beaches, Sci. Rep., 8, 6641, https://doi.org/10.1038/s41598-018-24630-6, 2018.
Marcos, M. and Woodworth, P. L.: Spatiotemporal changes in extreme sea levels along the coasts of the North Atlantic and the Gulf of Mexico, J. Geophys. Res.-Oceans, 122, 7031–7048, 2017.
McNamara, K. E. and Des Combes, H. J.: Planning for Community Relocations Due to Climate Change in Fiji, Int. J. Disast. Risk Sc., 6, 315–319, 2015.
Mengel, M., Treu, S., Lange, S., and Frieler, K.: ATTRICI v1.1 – counterfactual climate for impact attribution, Geosci. Model Dev., 14, 5269–5284, https://doi.org/10.5194/gmd-14-5269-2021, 2021.
Menéndez, M. and Woodworth, P. L.: Changes in extreme high water levels based on a quasi-global tide-gauge data set, J. Geophys. Res., 115, C10011, https://doi.org/10.1029/2009jc005997, 2010.
Mentaschi, L., Vousdoukas, M. I., Pekel, J.-F., Voukouvalas, E., and Feyen, L.: Global long-term observations of coastal erosion and accretion, Sci. Rep., 8, 12876, https://doi.org/10.1038/s41598-018-30904-w, 2018.
Merrifield, M. A., Genz, A. S., Kontoes, C. P., and Marra, J. J.: Annual maximum water levels from tide gauges: Contributing factors and geographic patterns, J. Geophys. Res.-Oceans, 118, 2535–2546, 2013.
Mudelsee, M.: Trend analysis of climate time series: A review of methods, Earth-Sci. Rev., 190, 310–322, 2019.
Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C. J. H., and Ward, P. J.: A global reanalysis of storm surges and extreme sea levels, Nat. Commun., 7, 11969, https://doi.org/10.1038/ncomms11969, 2016.
Muis, S., Apecechea, M. I., Dullaart, J., de Lima Rego, J., Madsen, K. S., Su, J., Yan, K., and Verlaan, M.: A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections, Front. Mar. Sci., 7, 263, https://doi.org/10.3389/fmars.2020.00263, 2020.
Muis, S., Dangendorf, S., Irazoqui Apecechea, M., Dullaart, J., de Lima Rego, J., Madsen, K. S., Su, J., Yan, K., Verlaan, M., Hay, C., Calafat, F. M., Marcos, M., Piecuch, C., Berk, K., Jensen, J., and Treu, S.: Input data for: Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.8322750, 2023.
Neumann, B., Vafeidis, A. T., Zimmermann, J., and Nicholls, R. J.: Future Coastal Population Growth and Exposure to Sea-Level Rise and Coastal Flooding – A Global Assessment, PLoS One, 10, e0118571, https://doi.org/10.1371/journal.pone.0118571, 2015.
Nicholls, R. J., Lincke, D., Hinkel, J., Brown, S., Vafeidis, A. T., Meyssignac, B., Hanson, S. E., Merkens, J.-L., and Fang, J.: A global analysis of subsidence, relative sea-level change and coastal flood exposure, Nat. Clim. Change, 11, 338–342, 2021.
Oelsmann, J., Marcos, M., Passaro, M., Sanchez, L., Dettmering, D., Dangendorf, S., and Seitz, F.: Regional variations in relative sea-level changes influenced by nonlinear vertical land motion, Nat. Geosci., 17, 137–144, https://doi.org/10.1038/s41561-023-01357-2, 2024.
Oelsmann, J., Marcos, M., Passaro, M., Sanchez, L., Dettmering, D., Dangendorf, S., and Seitz, F.: Data supplement to 'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900–2150' (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.8308347, 2023.
O'Neill, B., van Aalst, M., Zaiton Ibrahim, Z., Berrang Ford, L., Bhadwal, S., Buhaug, H., Diaz, D., Frieler, K., Garschagen, M., Magnan, A., Midgley, G., Mirzabaev, A., Thomas, A., and Warren, R.: Key Risks Across Sectors and Regions, in: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H. O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., Cambridge University Press, Cambridge, UK and New York, USA, 2411–2538, https://doi.org/10.1017/9781009325844.025, 2022a.
O'Neill, B., van Aalst, M., Zaiton Ibrahim, Z., Berrang Ford, L., Bhadwal, S., Buhaug, H., Diaz, D., Frieler, K., Garschagen, M., Magnan, A., Midgley, G., Mirzabaev, A., Thomas, A., and Warren, R.: Key Risks Across Sectors and Regions Supplementary Material, in: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H. O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., Cambridge University Press, Cambridge, UK and New York, USA, https://www.ipcc.ch/report/ar6/wg2/ (last access: 22 February 2024), 2022b.
Permanent Service for Mean Sea Level (PSMSL): Tide Gauge Data, [data set], https://psmsl.org/data/optaining/year_end/2022 (last access: 21 February 2024), 2022.
Pfeffer, J., Spada, G., Mémin, A., Boy, J.-P., and Allemand, P.: Decoding the origins of vertical land motions observed today at coasts, Geophys. J. Int., 210, 148–165, 2017.
Ranasinghe, R., Ruane, A. C., Vautard, R., Arnell, N., Coppola, E., Cruz, F. A., Dessai, S., Islam, A. S., Rahimi, M., Ruiz Carrascal, D., Sillmann, J., Sylla, M. B., Tebaldi, C., Wang, W., and Zaaboul, R.: Climate Change Information for Regional Impact and for Risk Assessment, 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, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1767–1926, https://doi.org/10.1017/9781009157896.014, 2021.
Riva, R. E. M., Frederikse, T., King, M. A., Marzeion, B., and van den Broeke, M. R.: Brief communication: The global signature of post-1900 land ice wastage on vertical land motion, The Cryosphere, 11, 1327–1332, https://doi.org/10.5194/tc-11-1327-2017, 2017.
Sharples, C., Walford, H., Watson, C., Ellison, J. C., Hua, Q., Bowden, N., and Bowman, D.: Ocean Beach, Tasmania: A swell-dominated shoreline reaches climate-induced recessional tipping point?, Mar. Geol., 419, 106081, https://doi.org/10.1016/j.margeo.2019.106081, 2020.
Slangen, A. B. A., Church, J. A., Agosta, C., Fettweis, X., Marzeion, B., and Richter, K.: Anthropogenic forcing dominates global mean sea-level rise since 1970, Nat. Clim. Change, 6, 701–705, 2016.
Spada, G.: Glacial Isostatic Adjustment and Contemporary Sea Level Rise: An Overview, Surv. Geophys., 38, 153–185, 2017.
Strauss, B. H., Orton, P. M., Bittermann, K., Buchanan, M. K., Gilford, D. M., Kopp, R. E., Kulp, S., Massey, C., de Moel, H., and Vinogradov, S.: Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change, Nat. Commun., 12, 2720, https://doi.org/10.1038/s41467-021-22838-1, 2021.
Tellman, B., Sullivan, J. A., Kuhn, C., Kettner, A. J., Doyle, C. S., Brakenridge, G. R., Erickson, T. A., and Slayback, D. A.: Satellite imaging reveals increased proportion of population exposed to floods, Nature, 596, 80–86, 2021.
Thompson, P. R. and Merrifield, M. A.: A unique asymmetry in the pattern of recent sea level change, Geophys. Res. Lett., 41, 7675–7683, 2014.
Tiggeloven, T., de Moel, H., Winsemius, H. C., Eilander, D., Erkens, G., Gebremedhin, E., Diaz Loaiza, A., Kuzma, S., Luo, T., Iceland, C., Bouwman, A., van Huijstee, J., Ligtvoet, W., and Ward, P. J.: Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures, Nat. Hazards Earth Syst. Sci., 20, 1025–1044, https://doi.org/10.5194/nhess-20-1025-2020, 2020.
Treu, S.: Source code of: Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution, Zenodo [data set], https://doi.org/10.5281/zenodo.10359838, 2023.
Treu, S., Muis, S., Dangendorf, S., Wahl, T., Oelsmann, J., Heinicke, S., Frieler, K., and Mengel, M.: Hourly Coastal water levels with Counterfactual (HCC), ISIMIP Repository [data set], https://doi.org/10.48364/ISIMIP.749905, 2023a.
Treu, S., Muis, S., Dangendorf, S., Wahl, T., Oelsmann, J., Heinicke, S., Frieler, K., and Mengel, M.: Water levels at tide gauges from: Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution, Zenodo [code, data set], https://doi.org/10.5281/zenodo.10354898, 2023b.
Van de Sande, B., Lansen, J., and Hoyng, C.: Sensitivity of Coastal Flood Risk Assessments to Digital Elevation Models, Water, 4, 568–579, 2012.
Vernimmen, R. and Hooijer, A.: New LiDAR-based elevation model shows greatest increase in global coastal exposure to flooding to be caused by early-stage sea-level rise, Earths Future, 11, e2022EF002880, https://doi.org/10.1029/2022ef002880, 2023.
Vousdoukas, M. I., Mentaschi, L., Hinkel, J., Ward, P. J., Mongelli, I., Ciscar, J.-C., and Feyen, L.: Economic motivation for raising coastal flood defenses in Europe, Nat. Commun., 11, 1–11, 2020.
Wang, J., Church, J. A., Zhang, X., and Chen, X.: Reconciling global mean and regional sea level change in projections and observations, Nat. Commun., 12, 990, https://doi.org/10.1038/s41467-021-21265-6, 2021.
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, 2016.
Wöppelmann, G. and Marcos, M.: Vertical land motion as a key to understanding sea level change and variability, Rev. Geophys., 54, 64–92, 2016.
Yang, Q., Shen, X., Anagnostou, E. N., Mo, C., Eggleston, J. R., and Kettner, A. J.: A High-Resolution Flood Inundation Archive (2016–the Present) from Sentinel-1 SAR Imagery over CONUS, B. Am. Meteor. Soc., 102, E1064–E1079, 2021.
Zhu, Y., Mitchum, G. T., Thompson, P. R., and Lagerloef, G. S. E.: Diagnosis of large-scale, low-frequency sea level variability in the northeast pacific ocean, J. Geophys. Res.-Oceans, 126, e2020JC016682, https://doi.org/10.1029/2020jc016682, 2021.
Short summary
This article describes a reconstruction of monthly coastal water levels from 1900–2015 and hourly data from 1979–2015, both with and without long-term sea level rise. The dataset is based on a combination of three datasets that are focused on different aspects of coastal water levels. Comparison with tide gauge records shows that this combination brings reconstructions closer to the observations compared to the individual datasets.
This article describes a reconstruction of monthly coastal water levels from 1900–2015 and...
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