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Strong regional trends in extreme weather over the next two decades under high- and low-emissions pathways

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Abstract

Global warming is rapidly shifting climate conditions away from what societies and ecosystems are adapted to. While the magnitude of changes in mean and extreme climate are broadly studied, regional rates of change, a key driver of climate risk, have received less attention. Here we show, using large ensembles of climate model simulations, that large parts of the tropics and subtropics, encompassing 70% of current global population, are expected to experience strong (>2 s.d.) joint rates of change in temperature and precipitation extremes combined over the next 20 years, under a high-emissions scenario, dropping to 20% under strong emissions mitigation. This is dominated by temperature extremes, with most of the world experiencing unusual (>1 s.d.) rates relative to the pre-industrial period, but unusual changes also occur for precipitation extremes in northern high latitudes, southern and eastern Asia and equatorial Africa. However, internal variability is high for 20 year trends, meaning that in the near term, trends of the opposite sign are still likely for precipitation extremes, and rare but not impossible for temperature extremes. We also find that rapid clean-up of aerosol emissions, mostly over Asia, leads to accelerated co-located increases in warm extremes and influences the Asian summer monsoons.

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Fig. 1: Near-term trends in extremes indices compared with PI trends.
Fig. 2: Regional joint near-term trends in TXx and Rx5day.
Fig. 3: Spatial patterns of near-term joint rates of change in extremes, and their components.

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Data availability

The climate model data used for this analysis are publicly available from the ESGF portals, for example, https://esgf-data.dkrz.de/search/cmip6-dkrz/. ETCCDI indices for CMIP6 models are available from the Copernicus Climate Data Store at https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-extreme-indices-cmip6?tab=overview (ref. 46), with additional ensemble members calculated for this analysis available from Zenodo (https://doi.org/10.5281/zenodo.12704988) (ref. 47). ERA5 temperature and precipitation data are available from https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview (ref. 48). REGEN-LONG is available from https://doi.org/10.25914/5ca4c2c6527d2 (ref. 49) and REGEN-ALL from https://doi.org/10.25914/5ca4c380b0d44 (ref. 50). Population data are available from https://sedac.ciesin.columbia.edu/data/collection/gpw-v4 (refs. 31,45).

Code availability

The code used in this analysis is publicly available from Zenodo (https://zenodo.org/records/12704988) (ref. 47).

References

  1. IPCC: Summary for Policymakers. In Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896.001

  2. Gulev, S. K. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 287–422 (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896.004

  3. Samset, B. H. et al. Steady global surface warming from 1973 to 2022 but increased warming rate after 1990. Commun. Earth Environ. 4, 400 (2023).

    Article  Google Scholar 

  4. Smith, S. J., Edmonds, J., Hartin, C. A., Mundra, A. & Calvin, K. Near-term acceleration in the rate of temperature change. Nat. Clim. Change 5, 333–336 (2015).

    Article  Google Scholar 

  5. Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1055 (2009).

    Article  CAS  Google Scholar 

  6. O’Neill, B. C. & Oppenheimer, M. Climate change impacts are sensitive to the concentration stabilization path. Proc. Natl Acad. Sci. USA 101, 16411–16416 (2004).

    Article  Google Scholar 

  7. Fischer, E. M., Sippel, S. & Knutti, R. Increasing probability of record-shattering climate extremes. Nat. Clim. Change 11, 689–695 (2021).

    Article  Google Scholar 

  8. Philip, S. Y. et al. Rapid attribution analysis of the extraordinary heat wave on the Pacific coast of the US and Canada in June 2021. Earth Syst. Dyn. 13, 1689–1713 (2022).

    Article  Google Scholar 

  9. Ranasinghe, R. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 1767–1926 (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896.014

  10. Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).

    Article  Google Scholar 

  11. Seneviratne, S. I. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 1513–1766 (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896.013

  12. IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896

  13. Sedláček, J. & Knutti, R. Half of the world’s population experience robust changes in the water cycle for a 2 °C warmer world. Environ. Res. Lett. 9, 044008 (2014).

    Article  Google Scholar 

  14. Lehner, F. & Stocker, T. F. From local perception to global perspective. Nat. Clim. Change 5, 731–734 (2015).

    Article  Google Scholar 

  15. Chavaillaz, Y., Joussaume, S., Dehecq, A., Braconnot, P. & Vautard, R. Investigating the pace of temperature change and its implications over the twenty-first century. Climatic Change 137, 187–200 (2016).

    Article  Google Scholar 

  16. Iturbide, M. et al. An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets. Earth Syst. Sci. Data 12, 2959–2970 (2020).

    Article  Google Scholar 

  17. Sanderson, B. M., Oleson, K. W., Strand, W. G., Lehner, F. & O’Neill, B. C. A new ensemble of GCM simulations to assess avoided impacts in a climate mitigation scenario. Climatic Change 146, 303–318 (2018).

    Article  Google Scholar 

  18. Hawkins, E. & Sutton, R. Time of emergence of climate signals. Geophys. Res. Lett. 39, L01702 (2012).

    Article  Google Scholar 

  19. King, A. D. et al. The timing of anthropogenic emergence in simulated climate extremes. Environ. Res. Lett. 10, 094015 (2015).

    Article  Google Scholar 

  20. Diffenbaugh, N. S. & Scherer, M. Observational and model evidence of global emergence of permanent, unprecedented heat in the 20th and 21st centuries. Climatic Change 107, 615–624 (2011).

    Article  Google Scholar 

  21. Chen, D. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 147–286 (Cambridge Univ. Press, 2021); https://doi.org/10.1017/9781009157896.003

  22. Mahlstein, I., Knutti, R., Solomon, S. & Portmann, R. W. Early onset of significant local warming in low latitude countries. Environ. Res. Lett. 6, 034009 (2011).

    Article  Google Scholar 

  23. Nguyen, T.-H., Min, S.-K., Paik, S. & Lee, D. Time of emergence in regional precipitation changes: an updated assessment using the CMIP5 multi-model ensemble. Clim. Dyn. 51, 3179–3193 (2018).

    Article  Google Scholar 

  24. Mahlstein, I., Portmann, R. W., Daniel, J. S., Solomon, S. & Knutti, R. Perceptible changes in regional precipitation in a future climate. Geophys. Res. Lett. 39, L05701 (2012).

    Article  Google Scholar 

  25. United Nations Framework Convention on Climate Change Paris Agreement (United Nations, 2015); https://unfccc.int/sites/default/files/resource/parisagreement_publication.pdf

  26. Wilcox, L. J. et al. Accelerated increases in global and Asian summer monsoon precipitation from future aerosol reductions. Atmos. Chem. Phys. 20, 11955–11977 (2020).

    Article  CAS  Google Scholar 

  27. Hawkins, E. & Sutton, R. The potential to narrow uncertainty in projections of regional precipitation change. Clim. Dyn. 37, 407–418 (2011).

    Article  Google Scholar 

  28. Lehner, F. et al. Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6. Earth Syst. Dyn. 11, 491–508 (2020).

    Article  Google Scholar 

  29. Persad, G. et al. Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments. Environ. Res. Clim. 2, 032001 (2023).

    Article  Google Scholar 

  30. Schumacher, D. L. et al. Exacerbated summer European warming not captured by climate models neglecting long-term aerosol changes. Commun. Earth Environ. 5, 182 (2024).

    Article  Google Scholar 

  31. Gridded Population of the World, Version 4 (GPWv4): Population Density Adjusted to Match 2015 Revision UN WPP Country Totals, Revision 11 (CIESIN, 2018); https://doi.org/10.7927/H4F47M65

  32. Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).

    Article  Google Scholar 

  33. Mackallah, C. et al. ACCESS datasets for CMIP6: methodology and idealised experiments. J. South. Hemisph. Earth Syst. Sci. 72, 93–116 (2022).

    Article  Google Scholar 

  34. Mauritsen, T. et al. Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and its response to increasing CO2. J. Adv. Model. Earth Syst. 11, 998–1038 (2019).

    Article  Google Scholar 

  35. Swart, N. C. et al. CCCma CanESM5 Model Output Prepared for CMIP6 CMIP Historical (Earth System Grid Federation, 2019); https://doi.org/10.22033/ESGF/CMIP6.3610

  36. Döscher, R. et al. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6. Geosci. Model Dev. 15, 2973–3020 (2022).

    Article  Google Scholar 

  37. Wyser, K. et al. The SMHI Large Ensemble (SMHI-LENS) with EC-Earth3.3.1. Geosci. Model Dev. 14, 4781–4796 (2021).

    Article  Google Scholar 

  38. Meehl, G. A. et al. Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 Earth system models. Sci. Adv. 6, eaba1981 (2022).

    Article  Google Scholar 

  39. O’Neill, B. C. et al. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482 (2016).

    Article  Google Scholar 

  40. Sillmann, J., Kharin, V. V., Zhang, X., Zwiers, F. W. & Bronaugh, D. Climate extremes indices in the CMIP5 multimodel ensemble: part 1. Model evaluation in the present climate. J. Geophys. Res. Atmos. 118, 1716–1733 (2013).

    Article  Google Scholar 

  41. Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Article  Google Scholar 

  42. Contractor, S. et al. Rainfall Estimates on a Gridded Network (REGEN)—a global land-based gridded dataset of daily precipitation from 1950 to 2016. Hydrol. Earth Syst. Sci. 24, 919–943 (2020).

    Article  Google Scholar 

  43. Ziese, M. et al. GPCC Full Data Daily Version.2018 at 1.0°: Daily Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data (GPCC, 2018); https://doi.org/10.5676/DWD_GPCC/FD_D_V2018_100

  44. Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E. & Houston, T. G. An overview of the global historical climatology network-daily database. J. Atmos. Ocean. Technol. 29, 897–910 (2012).

    Article  Google Scholar 

  45. Gridded Population of the World, Version 4 (GPWv4): Population Count Adjusted to Match 2015 Revision of UN WPP Country Totals, Revision 11 (CIESIN, 2018); https://doi.org/10.7927/H4PN93PB

  46. Sandstad, M., Schwingshackl, C. & Iles, C. Climate Extreme Indices and Heat Stress Indicators Derived from CMIP6 Global Climate Projections (C3S CDS, 2022); 1https://doi.org/10.24381/cds.776e08bd

  47. Iles, C. E. Data and code archival for Iles et al. 2024, Nature Geoscience, ‘Strong regional trends in extreme weather over next two decades under high and low emission pathways’. Zenodo https://doi.org/10.5281/zenodo.12704988 (2024).

  48. Hersbach, H. et al. ERA5 Hourly Data on Single Levels from 1940 to Present (C3S CDS, 2023); https://doi.org/10.24381/cds.adbb2d47

  49. Contractor, S. Rainfall Estimates on a Gridded Network (REGEN) Based on Long-Term Station Data v.1–2019 (NCI Australia, 2019); https://doi.org/10.25914/5ca4c2c6527d2

  50. Contractor, S. Rainfall Estimates on a Gridded Network (REGEN) Based on All Station Data v.1–2019 (NCI Australia, 2019); https://doi.org/10.25914/5ca4c380b0d44

  51. Kim, Y.-H., Min, S.-K., Zhang, X., Sillmann, J. & Sandstad, M. Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Weather Clim. Extrem. 29, 100269 (2020).

    Article  Google Scholar 

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Acknowledgements

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements no. 101003826 through the CRiceS project (C.E.I., B.H.S., M.T.L., M.S.) and no. 820655 through the EXHAUSTION project (M.S.) and from the Norwegian Research Council through the projects CATHY (324182; C.E.I., B.H.S., M.T.L., N.S., L.J.W.) and QUISARC (248834; C.E.I., B.H.S., M.T.L.). We acknowledge the Centre for Advanced Study in Oslo, Norway, which funded and hosted our HETCLIF centre during the academic year of 2023/2024. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. We also acknowledge the ETCCDI indices for CMIP6 provided through the Copernicus Climate Data Store, documented in refs. 40,51.

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Authors and Affiliations

  1. CICERO Center for International Climate Research, Oslo, Norway

    Carley E. Iles, Bjørn H. Samset, Marit Sandstad, Nina Schuhen & Marianne T. Lund

  2. National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK

    Laura J. Wilcox

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Contributions

C.E.I. and B.H.S. conceived and designed the experiments. C.E.I. performed the experiments and analysed the data. M.S. contributed materials/analysis tools. C.E.I., B.H.S., M.S., N.S., L.J.W. and M.T.L. wrote the paper.

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Correspondence to Carley E. Iles.

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Nature Geoscience thanks Vikki Thompson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson, in collaboration with the Nature Geoscience team.

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Supplementary Information

Supplementary Figs. 1–26, Table 1 and text on rates of change in subsequent periods, effects of aerosol clean-up on near-term rates of change, model evaluation and results for CDD.

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Iles, C.E., Samset, B.H., Sandstad, M. et al. Strong regional trends in extreme weather over the next two decades under high- and low-emissions pathways. Nat. Geosci. 17, 845–850 (2024). https://doi.org/10.1038/s41561-024-01511-4

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