Articles | Volume 23, issue 11
https://doi.org/10.5194/nhess-23-3467-2023
© 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-23-3467-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Nov 2023
Research article |
| 14 Nov 2023
| 14 Nov 2023
Human displacements from Tropical Cyclone Idai attributable to climate change
Benedikt Mester
CORRESPONDING AUTHOR
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Thomas Vogt
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Seth Bryant
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Section 4.4. Hydrology, GFZ German Research Centre for Geosciences, Potsdam, Germany
Christian Otto
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Katja Frieler
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Jacob Schewe
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Related authors
No articles found.
Michel Bechtold, Benjamin Poschlod, Christian Otto, Jan Volkholz, Matthias Büchner, and Florian Zabel
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-227, https://doi.org/10.5194/essd-2026-227, 2026
Preprint under review for ESSD
Short summary
Short summary
Many climate impacts depend on weather changes within a single day, but most studies still use daily averages. We created a new global hourly climate data set by disaggregating established daily records while keeping them physically consistent. The data reveal clearer patterns in rainfall timing, dangerous heat exposure, and wind and sunlight for energy, and are also very important for land surface modeling, where hourly input improves water and energy balance simulations.
Detlef P. Van Vuuren, Brian C. O'Neill, Claudia Tebaldi, Benjamin M. Sanderson, Louise P. Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh M. N. Fall, Katja Frieler, Matthew J. Gidden, Laila K. Gohar, Annika Högner, Andrew D. Jones, Jarmo Kikstra, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camilla Mathison, Shahbaz Mehmood, Zebedee Nicholls, Luciana F. Prado, Qiang Zhang, Steven K. Rose, Alex C. Ruane, Marit Sandstad, Carl-Friedrich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna A. Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha S. Vishwanathan, Tokuta Yokohata, Marco Zecchetto, and Tilo Ziehn
Geosci. Model Dev., 19, 2627–2656, https://doi.org/10.5194/gmd-19-2627-2026, https://doi.org/10.5194/gmd-19-2627-2026, 2026
Short summary
Short summary
We propose a set of seven plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Robert Reinecke, Tanjila Akhter, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Wim Thiery, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
Geosci. Model Dev., 19, 523–542, https://doi.org/10.5194/gmd-19-523-2026, https://doi.org/10.5194/gmd-19-523-2026, 2026
Short summary
Short summary
Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP (The Inter-Sectoral Impact Model Intercomparison Project) groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
Aaron Buhrmann, Cecilia I. Nievas, Nivedita Sairam, James E. Daniell, Heidi Kreibich, and Seth Bryant
EGUsphere, https://doi.org/10.5194/egusphere-2025-5172, https://doi.org/10.5194/egusphere-2025-5172, 2025
Short summary
Short summary
Our research lays the groundwork for the next generation of disaster risk modelling by improving how building-level value and use are estimated across Germany. By testing multiple data sources and methods, we identify a transparent, adaptable approach that enhances forecasts of damage and recovery—helping protect lives, property, and communities.
Edna Johanna Molina Bacca, Miodrag Stevanović, Benjamin Leon Bodirsky, Jonathan Cornelis Doelman, Louise Parsons Chini, Jan Volkholz, Katja Frieler, Christopher Paul Oliver Reyer, George Hurtt, Florian Humpenöder, Kristine Karstens, Jens Heinke, Christoph Müller, Jan Philipp Dietrich, Hermann Lotze-Campen, Elke Stehfest, and Alexander Popp
Earth Syst. Dynam., 16, 753–801, https://doi.org/10.5194/esd-16-753-2025, https://doi.org/10.5194/esd-16-753-2025, 2025
Short summary
Short summary
Land-use change projections are vital for impact studies. This study compares updated land-use model projections, including CO2 fertilization among other upgrades, from the MAgPIE and IMAGE models under three scenarios, highlighting differences, uncertainty hotspots, and harmonization effects. Key findings include reduced bioenergy crop demand projections and differences in grassland area allocation and sizes, with socioeconomic–climate scenarios' largest effect on variance starting in 2030.
Katja Frieler, Stefan Lange, Jacob Schewe, Matthias Mengel, Simon Treu, Christian Otto, Jan Volkholz, Christopher P. O. Reyer, Stefanie Heinicke, Colin Jones, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Ryan Heneghan, Derek P. Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Dánnell Quesada Chacón, Kerry Emanuel, Chia-Ying Lee, Suzana J. Camargo, Jonas Jägermeyr, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Lisa Novak, Inga J. Sauer, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, Michel Bechtold, Robert Reinecke, Inge de Graaf, Jed O. Kaplan, Alexander Koch, and Matthieu Lengaigne
EGUsphere, https://doi.org/10.5194/egusphere-2025-2103, https://doi.org/10.5194/egusphere-2025-2103, 2025
Short summary
Short summary
This paper describes the experiments and data sets necessary to run historic and future impact projections, and the underlying assumptions of future climate change as defined by the 3rd round of the ISIMIP Project (Inter-sectoral Impactmodel Intercomparison Project, isimip.org). ISIMIP provides a framework for cross-sectorally consistent climate impact simulations to contribute to a comprehensive and consistent picture of the world under different climate-change scenarios.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
Short summary
Short summary
River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Seth Bryant, Heidi Kreibich, and Bruno Merz
Proc. IAHS, 386, 181–187, https://doi.org/10.5194/piahs-386-181-2024, https://doi.org/10.5194/piahs-386-181-2024, 2024
Short summary
Short summary
Our study found that simplifying data in flood risk models can introduce errors. We tested 344 damage functions and found errors up to 40 % of the total asset value. This means large-scale flood risk assessments may have significant errors due to the modelling approach. Our research highlights the need for more attention to data aggregation in flood risk models.
Simon Treu, Sanne Muis, Sönke Dangendorf, Thomas Wahl, Julius Oelsmann, Stefanie Heinicke, Katja Frieler, and Matthias Mengel
Earth Syst. Sci. Data, 16, 1121–1136, https://doi.org/10.5194/essd-16-1121-2024, https://doi.org/10.5194/essd-16-1121-2024, 2024
Short summary
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.
Seth Bryant, Guy Schumann, Heiko Apel, Heidi Kreibich, and Bruno Merz
Hydrol. Earth Syst. Sci., 28, 575–588, https://doi.org/10.5194/hess-28-575-2024, https://doi.org/10.5194/hess-28-575-2024, 2024
Short summary
Short summary
A new algorithm has been developed to quickly produce high-resolution flood maps. It is faster and more accurate than current methods and is available as open-source scripts. This can help communities better prepare for and mitigate flood damages without expensive modelling.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
Short summary
Short summary
We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
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
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
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.
Seth Bryant, Heather McGrath, and Mathieu Boudreault
Nat. Hazards Earth Syst. Sci., 22, 1437–1450, https://doi.org/10.5194/nhess-22-1437-2022, https://doi.org/10.5194/nhess-22-1437-2022, 2022
Short summary
Short summary
The advent of new satellite technologies improves our ability to study floods. While the depth of water at flooded buildings is generally the most important variable for flood researchers, extracting this accurately from satellite data is challenging. The software tool presented here accomplishes this, and tests show the tool is more accurate than competing tools. This achievement unlocks more detailed studies of past floods and improves our ability to plan for and mitigate disasters.
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
Short summary
Short summary
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.
Cited articles
Angélil, O., Perkins-Kirkpatrick, S., Alexander, L. V., Stone, D., Donat, M. G., Wehner, M., Shiogama, H., Ciavarella, A., and Christidis, N.: Comparing regional precipitation and temperature extremes in climate model and reanalysis products, Weather Clim. Extrem., 13, 35–43, https://doi.org/10.1016/j.wace.2016.07.001, 2016.
Archila Bustos, M. F., Hall, O., Niedomysl, T., and Ernstson, U.: A pixel level evaluation of five multitemporal global gridded population datasets: a case study in Sweden, 1990–2015, Popul. Environ., 42, 255–277, https://doi.org/10.1007/s11111-020-00360-8, 2020.
Atmospheric and Environmental Research & African Risk Capacity: Flood depictions: AER AFED v05r01, https://www.aer.com/weather-risk-management/floodscan-near-real-time-and-historical-flood-mapping/ (last access: 15 July 2022), March 2022.
Beal, L. M., Vialard, J., Roxy, M. K., Ravichandran, M, McPhaden, M. J., Feng, M., Lumpkin, R., Unnikrishnan, A. S., Lee, T., Sloyan, B., Andres, M., Subramanian, A. C., Yu, L., Lengaigne, M., Shinoda,T., Annamalai, H., Ummenhofer., C. C., Strutton, P., Masumoto, Y., Tozuka, T., Wiggert, J., Han, W., and Hood, R.: IndOOS-2: A roadmap to sustained observations of the Indian Ocean for 2020-203, CLIVAR-4/2019, GOOS-237, CLIVAR/IOC-GOOS Indian Ocean Region Panel (IORP), 206 pp., https://doi.org/10.36071/clivar.rp.4.2019, 2019.
Bergensia: Red Cross: 90 Percent of Beira in Mozambique Destroyed by Cyclone Idai, https://bergensia.com/red-cross-90-percent-of-beira-in-mozambique-destroyed-by (last access: 14 May 2023), 2019.
Bernhofen, M. V., Whyman, C., Trigg, M. A., Sleigh, P. A., Smith, A. M., Sampson, C. C., Yamazaki, D., Ward, P. J., Rudari, R., Pappenberger, F., Dottori, F., Salamon, P., and Winsemius, H. C.: A first collective validation of global fluvial flood models for major floods in Nigeria and Mozambique, Environ. Res. Lett., 13, 104007, https://doi.org/10.1088/1748-9326/aae014, 2018.
Bilskie, M. V. and Hagen, S. C.: Defining Flood Zone Transitions in Low-Gradient Coastal Regions, Geophys. Res. Lett., 45, 2761–2770, https://doi.org/10.1002/2018GL077524, 2018.
Bloemendaal, N., Haigh, I. D., de Moel, H., Muis, S., Haarsma, R. J., and Aerts, J. C. J. H.: Generation of a global synthetic tropical cyclone hazard dataset using STORM, Sci. Data, 7, 40, https://doi.org/10.1038/s41597-020-0381-2, 2020.
Bloemendaal, N., de Moel, H., Mol, J. M., Bosma, P. R. M., Polen, A. N., and Collins, J. M.: Adequately reflecting the severity of tropical cyclones using the new Tropical Cyclone Severity Scale, Environ. Res. Lett., 16, 014048, https://doi.org/10.1088/1748-9326/abd131, 2021.
Bloemendaal, N., de Moel, H., Martinez, A. B., Muis, S., Haigh, I. D., van der Wiel, K., Haarsma, R. J., Ward, P. J., Roberts, M. J., Dullaart, J. C. M., and Aerts, J. C. J. H.: A globally consistent local-scale assessment of future tropical cyclone risk, Sci. Adv., 8, eabm8438, https://doi.org/10.1126/sciadv.abm8438, 2022.
Blöschl, G., Hall, J., Viglione, A., Perdigão, R. A. P., Parajka, J., Merz, B., Lun, D., Arheimer, B., Aronica, G. T., Bilibashi, A., Boháč, M., Bonacci, O., Borga, M., Čanjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Frolova, N., Ganora, D., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S., Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J., Ledvinka, O., Macdonald, N., Mavrova-Guirguinova, M., Mediero, L., Merz, R., Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski, I., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J., Volpi, E., Wilson, D., Zaimi, K., and Živković, N.: Changing climate both increases and decreases European river floods, Nature, 573, 108–111, https://doi.org/10.1038/s41586-019-1495-6, 2019.
Bryant, S., McGrath, H., and Boudreault, M.: Gridded flood depth estimates from satellite-derived inundations, Nat. Hazards Earth Syst. Sci., 22, 1437–1450, https://doi.org/10.5194/nhess-22-1437-2022, 2022.
Cattaneo, C., Beine, M., Fröhlich, C. J., Kniveton, D., Martinez-Zarzoso, I., Mastrorillo, M., Millock, K., Piguet, E., and Schraven, B.: Human Migration in the Era of Climate Change, Rev. Environ. Econ. Policy, 13, 189–206, https://doi.org/10.1093/reep/rez008, 2019.
Chavas, D. R., Lin, N., Dong, W., and Lin, Y.: Observed Tropical Cyclone Size Revisited, J. Climate, 29, 2923–2939, https://doi.org/10.1175/JCLI-D-15-0731.1, 2016.
Church, J. A. and White, N. J.: Sea-Level Rise from the Late 19th to the Early 21st Century, Surv. Geophys., 32, 585–602, https://doi.org/10.1007/s10712-011-9119-1, 2011.
Church, J. A., White, N. J., Coleman, R., Lambeck, K., and Mitrovica, J. X.: Estimates of the Regional Distribution of Sea Level Rise over the 1950–2000 Period, J. Climate, 17, 2609–2625, https://doi.org/10.1175/1520-0442(2004)017<2609:EOTRDO>2.0.CO;2, 2004.
Church, J. A., Clark, P. U., Cazenave, A., Gregory, J. M., Jevrejeva, S., Levermann, A., Merrifield, M. A., Milne, G. A., Nerem, R. S., Nunn, P. D., Payne, A. J., Pfeffer, W. T., Stammer, D., and Unnikrishnan, A. S.: Sea Level Change, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1137–1216, https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter13_FINAL.pdf (last access: 27 October 2023), 2013.
Cissé, G., McLeman, R., Adams, H., Aldunce, P., Bowen, K., Campbell-Lendrum, D., Clayton, S., Ebi, K. L., Hess, J., Huang, C., Liu, Q., McGregor, G., Semenza, J., and Tirado, M. C.: Health, Wellbeing, and the Changing Structure of Communities, 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, NY, USA, 1041–1170, https://doi.org/10.1017/9781009325844.009, 2022.
CMEMS: Global ocean gridded L4 sea surface heights and derived variables reprocessed (1993–ongoing), EU Copernicus Marine Service, CMEMS, https://www.copernicus.eu/en/access-data/copernicus-services-catalogue/global-ocean-griddedl4-sea-surface-heights-and-derived (last access: 2 August 2021), 2021.
Cohen, S., Brakenridge, G. R., Kettner, A., Bates, B., Nelson, J., McDonald, R., Huang, Y.-F., Munasinghe, D., and Zhang, J.: Estimating Floodwater Depths from Flood Inundation Maps and Topography, J. Am. Water Resour. Assoc., 54, 847–858, https://doi.org/10.1111/1752-1688.12609, 2018.
Custer, R. and Nishijima, K.: Flood vulnerability assessment of residential buildings by explicit damage process modelling, Nat. Hazards, 78, 461–496, https://doi.org/10.1007/s11069-015-1725-7, 2015.
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, https://doi.org/10.1073/pnas.1616007114, 2017.
Desai, B., Bresch, D. N., Cazabat, C., Hochrainer-Stigler, S., Mechler, R., Ponserre, S., and Schewe, J.: Addressing the human cost in a changing climate, Science, 372, 1284–1287, https://doi.org/10.1126/science.abh4283, 2021.
Dullaart, J. C. M., Muis, S., Bloemendaal, N., Chertova, M. V., Couasnon, A., and Aerts, J. C. J. H.: Accounting for tropical cyclones more than doubles the global population exposed to low-probability coastal flooding, Commun. Earth Environ., 2, 135, https://doi.org/10.1038/s43247-021-00204-9, 2021.
Eilander, D., Couasnon, A., Leijnse, T., Ikeuchi, H., Yamazaki, D., Muis, S., Dullaart, J., Haag, A., Winsemius, H. C., and Ward, P. J.: A globally applicable framework for compound flood hazard modeling, Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, 2023.
Emanuel, K.: Increasing destructiveness of tropical cyclones over the past 30 years, Nature, 436, 686–688, https://doi.org/10.1038/nature03906, 2005.
Emanuel, K., Ravela, S., Vivant, E., and Risi, C.: A Statistical Deterministic Approach to Hurricane Risk Assessment, B. Am. Meteorol. Soc., 87, 299–314, https://doi.org/10.1175/BAMS-87-3-299, 2006.
Emanuel, K. A.: The dependence of hurricane intensity on climate, Nature, 326, 483–485, https://doi.org/10.1038/326483a0, 1987.
Emanuel, K. A.: Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century, P. Natl. Acad. Sci. USA, 110, 12219–12224, https://doi.org/10.1073/pnas.1301293110, 2013.
Emerton, R., Cloke, H., Ficchi, A., Hawker, L., de Wit, S., Speight, L., Prudhomme, C., Rundell, P., West, R., Neal, J., Cuna, J., Harrigan, S., Titley, H., Magnusson, L., Pappenberger, F., Klingaman, N., and Stephens, E.: Emergency flood bulletins for Cyclones Idai and Kenneth: A critical evaluation of the use of global flood forecasts for international humanitarian preparedness and response, Int. J. Disast. Risk Reduct., 50, 101811, https://doi.org/10.1016/j.ijdrr.2020.101811, 2020.
Foresight: Migration and Global Environmental Change, Final Project Report, https://www.gov.uk/government/publications/migration-and-global-environmental-change-future-challenges (last access: 4 January 2023), 2011.
Fowler, H. J., Lenderink, G., Prein, A. F., Westra, S., Allan, R. P., Ban, N., Barbero, R., Berg, P., Blenkinsop, S., Do, H. X., Guerreiro, S., Haerter, J. O., Kendon, E. J., Lewis, E., Schaer, C., Sharma, A., Villarini, G., Wasko, C., and Zhang, X.: Anthropogenic intensification of short-duration rainfall extremes, Nat. Rev. Earth Environ., 2, 107–122, https://doi.org/10.1038/s43017-020-00128-6, 2021.
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, 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: 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, UK and New York, NY, USA, 1211–1362, 2021.
Frame, D. J., Rosier, S. M., Noy, I., Harrington, L. J., Carey-Smith, T., Sparrow, S. N., Stone, D. A., and Dean, S. M.: Climate change attribution and the economic costs of extreme weather events: a study on damages from extreme rainfall and drought, Climatic Change, 162, 781–797, https://doi.org/10.1007/s10584-020-02729-y, 2020a.
Frame, D. J., Wehner, M. F., Noy, I., and Rosier, S. M.: The economic costs of Hurricane Harvey attributable to climate change, Climatic Change, 160, 271–281, https://doi.org/10.1007/s10584-020-02692-8, 2020b.
Freire, S., MacManus, K., Pesaresi, M., Doxsey-Whitfield, E., and Mills, J.: Development of new open and free multi-temporal global population grids at 250 m resolution, in: 19th AGILE Conference on Geographic Information Science, 14–17 June 2016, Helsinki, Finland, https://publications.jrc.ec.europa.eu/repository/handle/JRC100523 (last access: 27 October 2023), 2016.
GADM: Database of Global Administrative Areas, https://gadm.org/data.html (last access: 5 August 2020), 2018.
Galantowicz, J. F. and Picton, J.: Flood Mapping with Passive Microwave Remote Sensing: Current Capabilities and Directions for Future Development, in: Earth Observation for Flood Applications, Elsevier, 39–60, https://doi.org/10.1016/B978-0-12-819412-6.00003-1, 2021.
Garner, A.J., Mann, M. E., Emanuel, K. A., Kopp, R. E., Lin, N., Alley, R. B., Horton, B. P., DeConto, R. M., Donnelly, J. P., and Pollard, D.: Impact of climate change on New York City's coastal flood hazard: Increasing flood heights from the preindustrial to 2300 CE, P. Natl. Acad. Sci. USA, 114, 11861–11866, https://doi.org/10.1073/pnas.1703568114, 2017.
Geiger, T., Frieler, K., and Bresch, D. N.: A global historical data set of tropical cyclone exposure (TCE-DAT), Earth Syst. Sci. Data, 10, 185–194, https://doi.org/10.5194/essd-10-185-2018, 2018.
Gemenne, F.: Why the numbers don't add up: A review of estimates and predictions of people displaced by environmental changes, Global Environ. Change, 21, S41–S49, https://doi.org/10.1016/j.gloenvcha.2011.09.005, 2011.
Google Maps: Mozambique, Satellite image, Google Maps [data set], https://www.google.com/maps/place/Mozambique/@-18.3359987,25.1264933,2875812m/data=!3m1!1e3!4m6!3m5!1s0x18d4aceae6fd4ac5:0x12bbbfb9ae16a115!8m2!3d-18.665695!4d35.529562!16zL20vMDR3bGg?entry=ttu (last access: 27 April 2022), 2022a.
Google Maps: Greater Area of Beira, Mozambique, Satellite image, Google Maps [data set], https://www.google.com/maps/place/Beira,+Mozambique/@-19.7768616,34.7865512,22273m/data=!3m2!1e3!4b1!4m6!3m5!1s0x1f2a6a5f5da047c1:0xa1d3dd2e50b3b6e6!8m2!3d-19.8315949!4d34.8370183!16zL20vMDNtajFk?entry=ttu (last access: 27 April 2022), 2022b.
Gudmundsson, L., Boulange, J., Do, H. X., Gosling, S. N., Grillakis, M. G., Koutroulis, A. G., Leonard, M., Liu, J., Müller Schmied, H., Papadimitriou, L., Pokhrel, Y., Seneviratne, S. I., Satoh, Y., Thiery, W., Westra, S., Zhang, X., and Zhao, F.: Globally observed trends in mean and extreme river flow attributed to climate change, Science, 371, 1159–1162, https://doi.org/10.1126/science.aba3996, 2021.
Guerreiro, S. B., Fowler, H. J., Barbero, R., Westra, S., Lenderink, G., Blenkinsop, S., Lewis, E., and Li, X.-F.: Detection of continental-scale intensification of hourly rainfall extremes, Nat. Clim. Change, 8, 803–807, https://doi.org/10.1038/s41558-018-0245-3, 2018.
Guha-Sapir, D., Below, R., and Hoyois, P.: EM-DAT: The CRED/OFDA International Disaster Database, Université Catholique de Louvain-Brussels, Belgium, https://www.emdat.be/ (last access: 21 April 2022), 2022.
Gulev, S. K., Thorne, P. W., Ahn, J., Dentener, F. J., Domingues, C. M., Gerland, S., Gong, D., Kaufman, D. S., Nnamchi, H. C., Quaas, J., Rivera, J. A., Sathyendranath, S., Smith, S. L., Trewin, B., von Schuckmann, K., and Vose, R. S.: Changing State of the Climate System., 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, 287–422, https://doi.org/10.1017/9781009157896.004, 2021.
Han, W., Meehl, G. A., Rajagopalan, B., Fasullo, J. T., Hu, A., Lin, J., Large, W. G., Wang, J., Quan, X.-W., Trenary, L. L., Wallcraft, A., Shinoda, T., and Yeager, S.: Patterns of Indian Ocean sea-level change in a warming climate, Nat. Geosci., 3, 546–550, https://doi.org/10.1038/ngeo901, 2010.
Hawker, L., Rougier, J., Neal, J., Bates, P., Archer, L., and Yamazaki, D.: Implications of Simulating Global Digital Elevation Models for Flood Inundation Studies, Water Resour. Res., 54, 7910–7928, https://doi.org/10.1029/2018WR023279, 2018.
HDX: Mozambique admin level 4 – Beira and Dondo neighbourhood boundaries, https://data.humdata.org/dataset/mozambique-admin-level-4-beira-and-dondo-neighbourhood (last access: 3 May 2022), 2019.
Holland, G. J.: An Analytic Model of the Wind and Pressure Profiles in Hurricanes, Mon. Weather Rev., 108, 1212–1218, https://doi.org/10.1175/1520-0493(1980)108<1212:AAMOTW>2.0.CO;2, 1980.
Hollinger, M. and Sienkevych, O.: The role of local and regional governments in protecting internally displaced persons (IDPs), https://rm.coe.int/the-role-of-local-and-regional-governments-in-protecting, (last access: 25 April 2023), 2019.
IDMC: Unveiling the cost of internal displacement, URL:https://www.internal-displacement.org/sites/default/files/publications/documents/201902-economic-impact-cost-estimates.pdf (last access: 25 April 2023), 2019.
INGC: REACH Initiative, Mozambique admin level 4 – Beira and Dondo neighbourhood boundaries, INGC [data set], https://data.humdata.org/dataset/mozambique-admin-level-4-beira-and-dondo-neighbourhood, (last access: 3 May 2022), 2019.
IDMC: IDMC Global Report on Internal Displacement 2022 Displacement Dataset, https://www.internal-displacement.org/database/displacement-data (last access: 12 February 2023), 2022.
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, Climatic Change, 122, 635–649, https://doi.org/10.1007/s10584-013-1011-1, 2014.
Kam, P. M., Aznar-Siguan, G., Schewe, J., Milano, L., Ginnetti, J., Willner, S., McCaughey, J. W., and Bresch, D. N.: Global warming and population change both heighten future risk of human displacement due to river floods, Environ. Res. Lett., 16, 044026, https://doi.org/10.1088/1748-9326/abd26c, 2021.
Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J., and Neumann, C. J.: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying Tropical Cyclone Data, B. Am. Meteorol. Soc., 91, 363–376, 2010.
Knutson, T., Camargo, S. J., Chan, J. C. L., Emanuel, K., Ho, C.-H., Kossin, J., Mohapatra, M., Satoh, M., Sugi, M., Walsh, K., and Wu, L.: Tropical Cyclones and Climate Change Assessment: Part I: Detection and Attribution, B. Am. Meteorol. Soc., 100, 1987–2007, https://doi.org/10.1175/BAMS-D-18-0189.1, 2019.
Knutson, T., Camargo, S. J., Chan, J. C. L., Emanuel, K., Ho, C.-H., Kossin, J., Mohapatra, M., Satoh, M., Sugi, M., Walsh, K., and Wu, L.: Tropical Cyclones and Climate Change Assessment: Part II: Projected Response to Anthropogenic Warming, B. Am. Meteorol. Soc., 101, E303–E322, https://doi.org/10.1175/BAMS-D-18-0194.1, 2020.
Knutson, T. R., Sirutis, J. J., Zhao, M., Tuleya, R. E., Bender, M., Vecchi, G. A., Villarini, G., and Chavas, D.: Global Projections of Intense Tropical Cyclone Activity for the Late Twenty-First Century from Dynamical Downscaling of CMIP5/RCP4.5 Scenarios, J. Climate, 28, 7203–7224, https://doi.org/10.1175/JCLI-D-15-0129.1, 2015.
Kossin, J. P., Knapp, K. R., Vimont, D. J., Murnane, R. J., and Harper, B. A.: A globally consistent reanalysis of hurricane variability and trends, Geophys. Res. Lett., 34, L04815, https://doi.org/10.1029/2006GL028836, 2007.
Kossin, J. P., Olander, T. L., and Knapp, K. R.: Trend Analysis with a New Global Record of Tropical Cyclone Intensity, J. Climate, 26, 9960–9976, https://doi.org/10.1175/JCLI-D-13-00262.1, 2013.
Kulp, S. A. and Strauss, B. H.: CoastalDEM: A global coastal digital elevation model improved from SRTM using a neural network, Remote Sens. Environ., 206, 231–239, https://doi.org/10.1016/j.rse.2017.12.026, 2018.
Kulp, S. A. and Strauss, B. H.: CoastalDEM v2.1: A high-accuracy and high-resolution global coastal elevation model trained on ICESat-2 satellite lidar, Climate Central Scientific Report, 17 pp., https://assets.ctfassets.net/cxgxgstp8r5d/3f1LzJSnp7ZjFD4loDYnrA/71eaba2b8f8d642dd9a7e6581dce0c66/CoastalDEM_2.1_Scientific_Report_.pdf (last access: 10 May 2022), 2021.
Lee, J.-Y., Marotzke, J., Bala, G., Cao, L., Corti, S., Dunne, J. P., Engelbrecht, F., Fischer, E., Fyfe, J. C., Jones, C., Maycock, A., Mutemi, J., Ndiaye, O., Panickal, S., and Zhou, T.: Future Global Climate: Scenario-Based Projections and Near-Term Information, 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, UK and New York, NY, USA, 553–672, 2021.
Leyk, S., Gaughan, A. E., Adamo, S. B., de Sherbinin, A., Balk, D., Freire, S., Rose, A., Stevens, F. R., Blankespoor, B., Frye, C., Comenetz, J., Sorichetta, A., MacManus, K., Pistolesi, L., Levy, M., Tatem, A. J., and Pesaresi, M.: The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use, Earth Syst. Sci. Data, 11, 1385–1409, https://doi.org/10.5194/essd-11-1385-2019, 2019.
Lin, N., Emanuel, K., Oppenheimer, M., and Vanmarcke, E.: Physically based assessment of hurricane surge threat under climate change, Nat. Clim. Change, 2, 462–467, https://doi.org/10.1038/nclimate1389, 2012.
Lin, N., Lane, P., Emanuel, K. A., Sullivan, R. M., and Donnelly, J. P.: Heightened hurricane surge risk in northwest Florida revealed from climatological-hydrodynamic modeling and paleorecord reconstruction, J. Geophys. Res.-Atmos., 119, 8606–8623, https://doi.org/10.1002/2014JD021584, 2014.
Lindsay, J. B.: The Whitebox Geospatial Analysis Tools Project and Open-Access GIS, in: Proc. GIS Res. UK 22nd Annu. Conf. Univ. Glasg., 16–18 April 2014, Glasgow, UK, 2014.
Luu, L. N., Scussolini, P., Kew, S., Philip, S., Hariadi, M. H., Vautard, R., Van Mai, K., Van Vu, T., Truong, K. B., Otto, F., van der Schrier, G., van Aalst, M. K., and van Oldenborgh, G. J.: Attribution of typhoon-induced torrential precipitation in Central Vietnam, October 2020, Climatic Change, 169, 24, https://doi.org/10.1007/s10584-021-03261-3, 2021.
Lyard, F. H., Allain, D. J., Cancet, M., Carrère, L., and Picot, N.: FES2014 global ocean tide atlas: design and performance, Ocean Sci., 17, 615–649, https://doi.org/10.5194/os-17-615-2021, 2021.
Mandli, K. T. and Dawson, C. N.: Adaptive mesh refinement for storm surge, Ocean Model., 75, 36–50, https://doi.org/10.1016/j.ocemod.2014.01.002, 2014.
McAdam, J.: Evacuations: a form of disaster displacement?, Forced Migr. Rev., 56–57, https://www.fmreview.org/sites/fmr/files/FMRdownloads/en/climate-crisis/mcadam.pdf (last access: 19 April 2023), 2022.
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.
Mester, B., Willner, S. N., Frieler, K., and Schewe, J.: Evaluation of river flood extent simulated with multiple global hydrological models and climate forcings, Environ. Res. Lett., 16, 094010, https://doi.org/10.1088/1748-9326/ac188d, 2021.
Mester, B., Vogt, T., Bryant, S., Otto, C., Frieler, K., and Schewe, J.: Source code for the study “Human displacements from Tropical Cyclone Idai attributable to climate change”, Zenodo [code], https://doi.org/10.5281/zenodo.10027136, 2023a.
Mester, B., Vogt, T., Bryant, S., Otto, C., Frieler, K., and Schewe, J.: Data collection for the study “Human displacements from Tropical Cyclone Idai attributable to climate change”, Zenodo [data set]. https://doi.org/10.5281/zenodo.10038190, 2023b.
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, https://doi.org/10.3389/fmars.2020.00263, 2020.
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, https://doi.org/10.1038/s41558-021-00993-z, 2021.
Nott, J. and Hayne, M.: High frequency of `super-cyclones' along the Great Barrier Reef over the past 5,000 years, Nature, 413, 508–512, https://doi.org/10.1038/35097055, 2001.
OCHA: Guiding Principles on Internal Displacement, https://reliefweb.int/report/world/guiding-principles-internal-displacement-2004 (last access: 14 February 2023), 2004.
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, 2022.
Otto, F. E. L., Harrington, L., Schmitt, K., Philip, S., Kew, S., van Oldenborgh, G. J., Singh, R., Kimutai, J., and Wolski, P.: Challenges to Understanding Extreme Weather Changes in Lower Income Countries, B. Am. Meteorol. Soc., 101, E1851–E1860, https://doi.org/10.1175/BAMS-D-19-0317.1, 2020.
Patricola, C. M. and Wehner, M. F.: Anthropogenic influences on major tropical cyclone events, Nature, 563, 339–346, https://doi.org/10.1038/s41586-018-0673-2, 2018.
Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422, https://doi.org/10.1038/nature20584, 2016.
Philip, S., Kew, S., van Oldenborgh, G. J., Otto, F., Vautard, R., van der Wiel, K., King, A., Lott, F., Arrighi, J., Singh, R., and van Aalst, M.: A protocol for probabilistic extreme event attribution analyses, Adv. Stat. Climatol. Meteorol. Oceanogr., 6, 177–203, https://doi.org/10.5194/ascmo-6-177-2020, 2020.
Probst, P. and Annunziato, A.: Tropical Cyclone IDAI: analysis of the wind, rainfall and storm surge impact, Join Research Centre, European Commission, https://www.humanitarianresponse.info/sites/www.humanitarianresponse.info/files/documents/files/joint_research_centre_analysis_of_wind_rainfall_and_storm_surge_impact_09_april_2019.pdf (last access: 7 November 2022), 2019.
QGIS.org: %Y. QGIS Geographic Information System, QGIS Association, http://www.qgis.org (last access: 20 August 2023), 2023.
ReliefWeb: Mozambique: Cyclone Idai & Floods Flash Update No. 10, 26 March 2019, https://reliefweb.int/report/mozambique/mozambique-cyclone-idai-floods-flash-update-no-10-26 (last access: 15 May 2023), 2019a.
ReliefWeb: `The First City Completely Devastated by Climate Change' Tries to Rebuild after Cyclone Idai, https://reliefweb.int/report/mozambique/first-city-completely-devastated-climate-change-tries-rebuild (last access: 7 November 2022), 2019b.
Resio, D. T. and Irish, J. L.: Tropical Cyclone Storm Surge Risk, in: Handbook of Coastal and Ocean Engineering, World Scientific, 1405–1422, https://doi.org/10.1142/9789813204027_0049, 2016.
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O'Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J. C., Kc, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D., Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G., Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M., Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A., and Tavoni, M.: The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environ. Change, 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009, 2017.
Sauer, I. J., Reese, R., Otto, C., Geiger, T., Willner, S. N., Guillod, B. P., Bresch, D. N., and Frieler, K.: Climate signals in river flood damages emerge under sound regional disaggregation, Nat. Commun., 12, 2128, https://doi.org/10.1038/s41467-021-22153-9, 2021.
Scherrer, S. C., Fischer, E. M., Posselt, R., Liniger, M. A., Croci-Maspoli, M., and Knutti, R.: Emerging trends in heavy precipitation and hot temperature extremes in Switzerland, J. Geophys. Res.-Atmos., 121, 2626–2637, https://doi.org/10.1002/2015JD024634, 2016.
Schiavina, M., Freire, S., and MacManus, K.: GHS population grid multitemporal (1975, 1990, 2000, 2015) R2019A, European Commission, JRC – Joint Research Centre [data set], https://doi.org/10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218, 2019.
Shen, X., Wang, D., Mao, K., Anagnostou, E., and Hong, Y.: Inundation Extent Mapping by Synthetic Aperture Radar: A Review, Remote Sens., 11, 879, https://doi.org/10.3390/rs11070879, 2019.
Shepherd, T. G.: A Common Framework for Approaches to Extreme Event Attribution, Curr. Clim. Change Rep., 2, 28–38, https://doi.org/10.1007/s40641-016-0033-y, 2016.
Shepherd, T. G., Boyd, E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West, I. M., Fowler, H. J., James, R., Maraun, D., Martius, O., Senior, C. A., Sobel, A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., van den Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., and Zenghelis, D. A.: Storylines: an alternative approach to representing uncertainty in physical aspects of climate change, Climatic Change, 151, 555–571, https://doi.org/10.1007/s10584-018-2317-9, 2018.
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.
Takayabu, I., Hibino, K., Sasaki, H., Shiogama, H., Mori, N., Shibutani, Y., and Takemi, T.: Climate change effects on the worst-case storm surge: a case study of Typhoon Haiyan, Environ. Res. Lett., 10, 064011, https://doi.org/10.1088/1748-9326/10/6/064011, 2015.
The World Bank: World Development Indicators. Population, total – Mozambique, https://data.worldbank.org/indicator/SP.POP.TOTL?end=2019&locations=MZ&start=2015 (last access: 29 April 2022), 2022.
Titley, D., Hegerl, G., Jacobs, K., Mote, P. W., Paciorek, C. J., Shepherd, J. M., Shepherd, T. G., Sobel, A. H., Walsh, J., and Zwiers, F. W.: Attribution of Extreme Weather Events in the Context of Climate Change, The National Academies Press, Washington, DC, https://doi.org/10.17226/21852, 2016.
Tozer, B., Sandwell, D. T., Smith, W. H. F., Olson, C., Beale, J. R., and Wessel, P.: Global Bathymetry and Topography at 15 Arc Sec: SRTM15+, Earth Space Sci., 6, 1847–1864, https://doi.org/10.1029/2019EA000658, 2019.
Trenberth, K. E., Fasullo, J. T., and Shepherd, T. G.: Attribution of climate extreme events, Nat. Clim. Change, 5, 725–730, https://doi.org/10.1038/nclimate2657, 2015.
van Berchum, E. C., van Ledden, M., Timmermans, J. S., Kwakkel, J. H., and Jonkman, S. N.: Rapid flood risk screening model for compound flood events in Beira, Mozambique, Nat. Hazards Earth Syst. Sci., 20, 2633–2646, https://doi.org/10.5194/nhess-20-2633-2020, 2020.
van den Hurk, B. J. J. M., Baldissera Pacchetti, M., Boere, E., Ciullo, A., Coulter, L., Dessai, S., Ercin, E., Goulart, H., Hamed, R., Hochrainer-Stigler, S., Koks, E., Kubiczek, P., Levermann, A., Mechler, R., van Meersbergen, M., Mester, B., Middelanis, R., Minderhoud, K., Mysiak, J., Nirandjan, S., van den Oord, G., Otto, C., Sayers, P., Schewe, J., Shepherd, T. G., Sillmann, J., Stuparu, D., Vogt, T., and Witpas, K.: Climate impact storylines for assessing socio-economic responses to remote events, Clim. Risk Manage., 40, 100500, https://doi.org/10.1016/j.crm.2023.100500, 2023.
van Oldenborgh, G. J., van der Wiel, K., Sebastian, A., Singh, R., Arrighi, J., Otto, F., Haustein, K., Li, S., Vecchi, G., and Cullen, H.: Attribution of extreme rainfall from Hurricane Harvey, August 2017, Environ. Res. Lett., 12, 124009, https://doi.org/10.1088/1748-9326/aa9ef2, 2017.
van Oldenborgh, G. J., van der Wiel, K., Kew, S., Philip, S., Otto, F., Vautard, R., King, A., Lott, F., Arrighi, J., Singh, R., and van Aalst, M.: Pathways and pitfalls in extreme event attribution, Climatic Change, 166, 13, https://doi.org/10.1007/s10584-021-03071-7, 2021.
Warren, M.: Why Cyclone Idai is one of the Southern Hemisphere's most devastating storms, Nature, https://doi.org/10.1038/d41586-019-00981-6, in press, 2019.
Webster, P. J., Holland, G. J., Curry, J. A., and Chang, H.-R.: Changes in Tropical Cyclone Number, Duration, and Intensity in a Warming Environment, Science, 309, 1844–1846, https://doi.org/10.1126/science.1116448, 2005.
Wessel, P. and Smith, W.: A global, self-consistent, hierarchical, high-resolution shoreline database, J. Geophys. Res., 101, 8741–8743, https://doi.org/10.1029/96JB00104, 1996.
Wulder, M. A., White, J. C., Loveland, T. R., Woodcock, C. E., Belward, A. S., Cohen, W. B., Fosnight, E. A., Shaw, J., Masek, J. G., and Roy, D. P.: The global Landsat archive: Status, consolidation, and direction, Remote Sens. Environ., 185, 271–283, 2016.
Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset, Water Resour. Res., 55, 5053–5073, https://doi.org/10.1029/2019WR024873, 2019.
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D., Maraun, D., Ramos, A. M., Ridder, N. N., Thiery, W., and Vignotto, E.: A typology of compound weather and climate events, Nat. Rev. Earth Environ., 1, 333–347, https://doi.org/10.1038/s43017-020-0060-z, 2020.
Short summary
In 2019, Cyclone Idai displaced more than 478 000 people in Mozambique. In our study, we use coastal flood modeling and satellite imagery to construct a counterfactual cyclone event without the effects of climate change. We show that 12 600–14 900 displacements can be attributed to sea level rise and the intensification of storm wind speeds due to global warming. Our impact attribution study is the first one on human displacement and one of very few for a low-income country.
In 2019, Cyclone Idai displaced more than 478 000 people in Mozambique. In our study, we use...
Altmetrics
Final-revised paper
Preprint