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Anthropogenic influences on major tropical cyclone events

Nature volume 563, pages 339–346 (2018)Cite this article

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Abstract

There is no consensus on whether climate change has yet affected the statistics of tropical cyclones, owing to their large natural variability and the limited period of consistent observations. In addition, projections of future tropical cyclone activity are uncertain, because they often rely on coarse-resolution climate models that parameterize convection and hence have difficulty in directly representing tropical cyclones. Here we used convection-permitting regional climate model simulations to investigate whether and how recent destructive tropical cyclones would change if these events had occurred in pre-industrial and in future climates. We found that, relative to pre-industrial conditions, climate change so far has enhanced the average and extreme rainfall of hurricanes Katrina, Irma and Maria, but did not change tropical cyclone wind-speed intensity. In addition, future anthropogenic warming would robustly increase the wind speed and rainfall of 11 of 13 intense tropical cyclones (of 15 events sampled globally). Additional regional climate model simulations suggest that convective parameterization introduces minimal uncertainty into the sign of projected changes in tropical cyclone intensity and rainfall, which allows us to have confidence in projections from global models with parameterized convection and resolution fine enough to include tropical cyclones.

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Fig. 1: Tropical cyclone tracks.
Fig. 2: Time series and boxplots of tropical cyclone maximum 10-m wind speed.
Fig. 3: Tropical cyclone rainfall composites.
Fig. 4: Probability density functions of tropical cyclone rainfall rates.

Data availability

Simulation data are available at the National Energy Research Scientific Computing Center (NERSC) at http://portal.nersc.gov/cascade/TC/.

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Acknowledgements

This material is based on work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division, Regional and Global Climate Modeling Program, under award number DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the US Department of Energy under contract number DE-AC02-05CH11231. We thank H. Krishnan for setting up access to the simulation data at NERSC.

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Nature thanks J. Manganello and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Authors and Affiliations

  1. Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Christina M. Patricola

  2. Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Michael F. Wehner

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  1. Christina M. Patricola
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Contributions

C.M.P. and M.F.W. conceived the project and developed the methodology. C.M.P. performed the simulations, with climate perturbations from M.F.W., and analysed the data. C.M.P. wrote the manuscript with contributions from M.F.W.

Corresponding author

Correspondence to Christina M. Patricola.

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Extended data figures and tables

Extended Data Fig. 1 Tropical cyclone tracks.

a, b, The observed hurricane track (black) with simulated tropical cyclone tracks from ten ensemble members (grey dashed lines) and the ensemble mean (grey solid line) of the historical simulation for hurricanes Irma (a) and Maria (b) at 4.5-km resolution.

Extended Data Fig. 2 Time series and boxplots of tropical cyclone minimum SLP.

a–c, The time series of minimum SLP (hPa) from observations (black) and the ensemble mean of the pre-industrial (blue), historical (grey) and RCP8.5 (red) simulations of hurricane Katrina at 3-km resolution (a) and hurricanes Irma (b) and Maria (c) at 4.5-km resolution. d–f, Boxplots of minimum SLP (hPa) from the ten-member ensemble of pre-industrial (blue), historical (black) and RCP8.5 (red) simulations of hurricane Katrina at 3-km, 9-km and 27-km resolution (d), and of hurricanes Irma (e) and Maria (f) at 4.5-km resolution. The centre line denotes the median, box limits denote lower and upper quartiles, and whiskers denote the minimum and maximum. The observed minimum SLP is marked with a horizontal black line. Simulations that used convective parameterization are denoted by asterisks.

Extended Data Fig. 3 Tropical cyclone minimum SLP.

Heatmaps are shown of the ensemble-mean difference in minimum SLP (in hPa) between the historical and pre-industrial simulations and between the RCP4.5, RCP6.0 and RCP8.5 simulations and the historical simulation (blue/red), with minimum SLP from observations and the ensemble-mean historical simulation (yellow/magenta). Light grey denotes substantial differences between the simulated and the observed tropical cyclone tracks and dark grey denotes simulations that were not performed. *Changes significant at the 10% level; **changes significant at the 5% level. Simulations that used convective parameterization are denoted ‘P’.

Extended Data Fig. 4 Tropical cyclone rainfall composites.

a–d, Rainfall rate (colour scale, in millimetres per hour) relative to the tropical cyclone centre and throughout the simulated tropical cyclone lifetime from the ensemble mean of the RCP6.0 minus historical simulation of hurricane Floyd (a) and the RCP8.5 minus historical simulation of cyclone Gafilo (b), typhoon Haiyan (c) and cyclone Yasi (d) at 4.5-km resolution. Contours denote the rainfall rate (in millimetres per hour) from the corresponding historical simulation. The axes show the number of model grid points from the tropical cyclone centre.

Extended Data Table 1 List of tropical cyclone events
Full size table

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Patricola, C.M., Wehner, M.F. Anthropogenic influences on major tropical cyclone events. Nature 563, 339–346 (2018). https://doi.org/10.1038/s41586-018-0673-2

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Keywords

  • Tropical Cyclones
  • Future Tropical Cyclone Activity
  • Lateral Boundary Conditions (LBCs)
  • NCEP Climate Forecast System Version
  • Simulated Tropical Cyclone Track

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