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Double benefit of limiting global warming for tropical cyclone exposure

Nature Climate Change volume 11, pages 861–866 (2021)Cite this article

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Abstract

Tropical cyclone (TC) impacts are expected to worsen under continued global warming and socio-economic development. Here we combine TC simulations with an impact model to quantify country-level population exposure to TC winds for different magnitudes of global mean surface temperature increase and future population distributions. We estimate an annual global TC exposure increase of 26% (33 million people) for a 1 °C increase in global mean surface temperature, assuming present-day population. The timing of warming matters when additionally accounting for population change, with global population projected to peak around mid-century and decline thereafter. A middle-of-the-road socio-economic scenario combined with 2 °C of warming around 2050 increases exposure by 41% (52 million). A stronger mitigation scenario reaching 2 °C around 2100 limits this increase to 20% (25 million). Rapid climate action therefore avoids interference with peak global population timing and limits climate-change-driven exposure. Cumulatively, over 1.8 billion people could be saved by 2100.

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Fig. 1: Increase in annual population exposure with GMST.
Fig. 2: Population exposure for different base years of socio-economic development and 2 °C of warming.
Fig. 3: Future population exposure for different warming scenarios.

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Data availability

The historical48 and future49 population data are freely available online. The historical TC exposure data are available from the Tropical Cyclone Exposure Database archive50. The TC track simulations are available for scientific purposes only and upon request from WindRiskTech (info@windrisktech.com). Requests regarding the CLIMADA impact model should be addressed to D.N.B. (dbresch@ethz.ch). The data to display country outlines and coastlines are based on the Generic Mapping Tools51. All remaining data that support the findings of this study are available from the corresponding author upon request.

Code availability

The simulations to quantify the TC impact were conducted using the Python tool CLIMADA, available at https://github.com/CLIMADA-project/climada_python/releases/tag/v2.2.0. In particular, the tool to generate the artificial TC exposure time series is freely available at https://github.com/CLIMADA-project/climada_petals/blob/main/doc/tutorial/climada_hazard_emulator.ipynb. The model to generate the TC tracks, the model to construct the temperature scenarios (MAGICC 6.8 and the climate module of the Potsdam Real-Time Integrated Model for the probabilistic assessment of emission paths (PRIMAP)) and the PRIMAP emissions module used for the creation and extension of the NDC pathways are proprietary and cannot be shared publicly. All remaining code that was used to analyse the data and produce the figures is available from the corresponding author upon request.

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Acknowledgements

We thank T. Vogt for his valuable contribution to reworking the emulator code and making it publicly available. We further thank the ISIMIP team for their support. T.G. acknowledges funding through the framework of the Leibniz Competition SAW-2016-PIK-1 (ENGAGE) and funding by the German Federal Ministry of Education and Research (BMBF) project FKZ:01LA1829A (SLICE). K.F. acknowledges funding for ISIMIP through the BMBF for research projects 01LS1201A2 (ISIMIP2b) and 01LS1711A (ISIpedia). J.G. acknowledges support from the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (16\_II\_148\_Global\_A\_IMPACT) and from the BMBF (01LS1711A). The content and views presented in this paper are solely those of the authors and do not necessarily represent the views of Deutscher Wetterdienst (DWD).

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Authors and Affiliations

  1. Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany

    Tobias Geiger, Johannes Gütschow & Katja Frieler

  2. Deutscher Wetterdienst (DWD), Climate and Environment Consultancy, Stahnsdorf, Germany

    Tobias Geiger

  3. Institute for Environmental Decisions, ETH Zurich, Zurich, Switzerland

    David N. Bresch

  4. Federal Office of Meteorology and Climatology MeteoSwiss, Zurich-Airport, Switzerland

    David N. Bresch

  5. Program in Atmospheres, Oceans and Climate, Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Kerry Emanuel

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Contributions

T.G. and K.F. conceived and designed the research. K.E. generated the TC simulations. D.N.B. conducted the impact simulations. J.G. provided the future warming scenarios. T.G. developed the software tool and analysed and interpreted the data with help from all authors. All authors contributed to the writing of the manuscript.

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Correspondence to Tobias Geiger.

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The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Cindy Bruyère, Ilan Noy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Normalized distribution of global annually exposed population from tropical cyclones.

The distributions are shown for two GMST levels (1 °C and 2 °C) and two fixed population patterns (2015 (observed) and 2050 (SSP2)) for modeled exposure (colored lines) based on RCP6.0 simulations compared to 1980–2015 observed exposure (black line). The logarithm of annual exposed population is binned for the observations (36 years, 12 bins) and for the simulations for all years falling in a 0.5 °C temperature interval around the desired GMST value (50 bins).

Extended Data Fig. 2 Annual population exposure with global mean surface temperature (GMST) for constant tropical cyclone frequency.

Same as Fig. 1 but with fixed TC frequency at 1 °C of warming compared to the pre-industrial level.

Supplementary information

Supplementary Information

Supplementary Fig. 1, Tables 1 and 2, and References.

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Geiger, T., Gütschow, J., Bresch, D.N. et al. Double benefit of limiting global warming for tropical cyclone exposure. Nat. Clim. Chang. 11, 861–866 (2021). https://doi.org/10.1038/s41558-021-01157-9

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