Climatic Change

, Volume 146, Issue 3–4, pp 455–470 | Cite as

Projected trends in high-mortality heatwaves under different scenarios of climate, population, and adaptation in 82 US communities

  • G. Brooke AndersonEmail author
  • Keith W. Oleson
  • Bryan Jones
  • Roger D. Peng


Some rare heatwaves have extreme daily mortality impacts; moderate heatwaves have lower daily impacts but occur much more frequently at present and so account for large aggregated impacts. We applied health-based models to project trends in high-mortality heatwaves, including proportion of all heatwaves expected to be high-mortality, using the definition that a high-mortality heatwave increases mortality risk by ≥20 %. We projected these trends in 82 US communities in 2061–2080 under two scenarios of climate change (RCP4.5, RCP8.5), two scenarios of population change (SSP3, SSP5), and three scenarios of community adaptation to heat (none, lagged, on-pace) for large- and medium-ensemble versions of the National Center for Atmospheric Research’s Community Earth System Model. More high-mortality heatwaves were expected compared to present under all scenarios except on-pace adaptation, and population exposure was expected to increase under all scenarios. At least seven more high-mortality heatwaves were expected in a twenty-year period in the 82 study communities under RCP8.5 than RCP4.5 when assuming no adaptation. However, high-mortality heatwaves were expected to remain <1 % of all heatwaves and heatwave exposure under all scenarios. Projections were most strongly influenced by the adaptation scenario—going from a scenario of on-pace to lagged adaptation or from lagged to no adaptation more than doubled the projected number of and exposure to high-mortality heatwaves. Based on our results, fewer high-mortality heatwaves are expected when following RCP4.5 versus RCP8.5 and under higher levels of adaptation, but high-mortality heatwaves are expected to remain a very small proportion of total heatwave exposure.



GB Anderson and RD Peng were supported by NIEHS grants R00ES022631 and R21ES020152 and by NSF grant 1331399. Material contributed by KW Oleson is based upon work supported by the National Science Foundation (Grant #AGS-1243095), in part by NASA grant NNX10AK79G (the SIMMER project), and by the NCAR Weather and Climate Impacts Assessment Science Program. We thank Brian O’Neill, Claudia Tebaldi, and two anonymous reviewers for helpful suggestions throughout.

Supplementary material

10584_2016_1779_MOESM1_ESM.docx (652 kb)
ESM 1 (DOCX 651 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Environmental & Radiological Health SciencesColorado State UniversityFort CollinsUSA
  2. 2.National Center for Atmospheric ResearchBoulderUSA
  3. 3.CUNY Institute for Demographic ResearchNew YorkUSA
  4. 4.Johns Hopkins Bloomberg School of Public HealthBaltimoreUSA

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