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Impacts of the North Atlantic subtropical high on interannual variation of summertime heat stress over the conterminous United States

  • Wenhong LiEmail author
  • Tian Zou
  • Laifang Li
  • Yi Deng
  • Victor T. Sun
  • Qinghong Zhang
  • J. Bradley Layton
  • Soko Setoguchi
Article

Abstract

Heat index (HI) provides a proven indicator of heat stress and discomfort for the general public. The index takes the integrated effects of both temperature and humidity into account, and both factors are regulated by large-scale circulation patterns. This study examines the impacts of the North Atlantic Subtropical High (NASH) on HI over the conterminous United States (CONUS). The analysis suggests that the HI is primarily controlled by surface air temperature over the CONUS; but is negatively correlated with relative humidity in the western and Central US north of 40°N. In addition, winds contribute to the variation of HI in the Midwest and the southeastern US. By regulating these meteorological parameters, the movement of the NASH western ridge significantly impacts HI over the US, especially the Southeast. When the NASH western ridge is located northwest (NW) of its climatological mean position, abnormally high temperatures are observed due to fewer clouds and a precipitation deficit, leading to positive HI anomalies over the southeastern US. In contrast, when the western ridge is located in the southwest (SW), temperature decreases and HI anomaly becomes negative over the Southeast, even though relative humidity increases east of 100°W. NASH has a weaker impact on the HI when it is far from the North American continent, especially during southeast (SE) ridge years. In the future, CMIP5 models project an increase in HI over the entire CONUS, while NASH-induced HI will be weakened during the NW, SE and NE ridge years but strengthened when its ridge moves to the SW quadrant. These results suggest that future increases in heat stress are likely caused by climatological warming and NASH intensification.

Keywords

US heat waves Heat index North Atlantic subtropical high NASH western ridges 

Notes

Acknowledgements

We thank the international modeling groups for providing their data for analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the model data, the JSC/CLIVAR Working Group on Coupled Modeling (WGCM) and their Coupled Model Intercomparison Project (CMIP) and Climate Simulation Panel for organizing the model data analysis activity, and the IPCC WG1 TSU for technical support. The IPCC Data Archive at Lawrence Livermore National Laboratory is supported by the Office of Science, US Department of Energy. This work is supported by the NIH Grant NIH-1R21AG044294-01A1. L Li is supported by the NSF PREEVENTS (grant number: NSF-ICER-1663138). 

Supplementary material

382_2019_4708_MOESM1_ESM.doc (1.1 mb)
Supplementary material 1 (DOC 1091 KB)

References

  1. Aguado E, Burt JE (2015) Understanding weather and climate, 7th edition. Pearson, LondonGoogle Scholar
  2. Arias PA, Fu R, Mo KC et al (2012) Decadal variation of rainfall seasonality in the North American Monsoon region and its potential causes. J Clim 25:4258–4274.  https://doi.org/10.1175/JCLI-D-11-00140.1 CrossRefGoogle Scholar
  3. Berko J, Ingram DD, Saha S, Parker JD (2014) Deaths attributed to heat, cold, and other weather events in the United States, 2006–2010. Natl Health Stat Report 2014:1–15Google Scholar
  4. Biasutti M, Giannini A (2006) Robust Sahel drying in response to late 20th century forcings. Geophys Res Lett.  https://doi.org/10.1029/2006GL026067 Google Scholar
  5. Clement AC, Burgman R, Norris JR (2009) Observational and model evidence for positive low-level cloud feedback. Science 325:460–464.  https://doi.org/10.1126/science.1171255 CrossRefGoogle Scholar
  6. Dave AC by, Susan Lozier M, Barber RT et al (2012) Physical controls on low and mid-latitude marine primary productivityGoogle Scholar
  7. Davis RE, Hayden BP, Gay DA et al (1997) The North Atlantic subtropical anticyclone. J Clim 10:728–744.  https://doi.org/10.1175/1520-0442(1997)010%3C0728:TNASA%3E2.0.CO;2 CrossRefGoogle Scholar
  8. Easterling DR, Karl TR, Mason EH, Hughes PY, Bowman DP (1996) United States Historical Climatology Network (U.S. HCN) Monthly Temperature and Precipitation Data. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, TennesseeGoogle Scholar
  9. Gamble DW, Curtis S (2008) Caribbean precipitation: review, model and prospect. Prog Phys Geogr 32:265–276.  https://doi.org/10.1177/0309133308096027 CrossRefGoogle Scholar
  10. Ganguly AR, Steinhaeuser K, Erickson DJ et al (2009) Higher trends but larger uncertainty and geographic variability in 21st century temperature and heat waves. Proc Natl Acad Sci USA 106:15555–15559.  https://doi.org/10.1073/pnas.0904495106 CrossRefGoogle Scholar
  11. Gao Y, Fu JS, Drake JB et al (2012) Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system. Environ Res Lett 7:044025.  https://doi.org/10.1088/1748-9326/7/4/044025 CrossRefGoogle Scholar
  12. Gleckler PJ, Taylor KE, Doutriaux C (2008) Performance metrics for climate models. J Geophys Res Atmos.  https://doi.org/10.1029/2007JD008972 Google Scholar
  13. Grotjahn R, Black R, Leung R et al (2016) North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends. Clim Dyn 46:1151–1184.  https://doi.org/10.1007/s00382-015-2638-6 CrossRefGoogle Scholar
  14. Intergovernmental Panel on Climate Change (2014) Climate change 2013—the physical science basis: Working Group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  15. Kalnay E, Kanamitsu M, Kistler R et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471.  https://doi.org/10.1175/1520-0477(1996)077%3C0437:TNYRP%3E2.0.CO;2 CrossRefGoogle Scholar
  16. Knowlton K, Rotkin-Ellman M, King G et al (2009) The 2006 California heat wave: impacts on hospitalizations and emergency department visits. Environ Health Perspect 117:61–67.  https://doi.org/10.1289/ehp.11594 CrossRefGoogle Scholar
  17. Li W, Li L, Fu R et al (2011) Changes to the North Atlantic subtropical high and its role in the intensification of summer rainfall variability in the southeastern United States. J Clim 24:1499–1506.  https://doi.org/10.1175/2010JCLI3829.1 CrossRefGoogle Scholar
  18. Li L, Li W, Kushnir Y (2012a) Variation of the North Atlantic subtropical high western ridge and its implication to Southeastern US summer precipitation. Clim Dyn 39:1401–1412.  https://doi.org/10.1007/s00382-011-1214-y CrossRefGoogle Scholar
  19. Li W, Li L, Ting M, Liu Y (2012b) Intensification of Northern Hemisphere subtropical highs in a warming climate. Nat Geosci 5:830–834.  https://doi.org/10.1038/ngeo1590 CrossRefGoogle Scholar
  20. Li L, Li W, Deng Y (2013a) Summer rainfall variability over the Southeastern United States and its intensification in the 21st century as assessed by CMIP5 models. J Geophys Res Atmos 118:340–354.  https://doi.org/10.1002/jgrd.50136 CrossRefGoogle Scholar
  21. Li W, Li L, Ting M et al (2013b) Intensification of the Southern Hemisphere summertime subtropical anticyclones in a warming climate. Geophys Res Lett 40:5959–5964.  https://doi.org/10.1002/2013GL058124 CrossRefGoogle Scholar
  22. Li L, Li W, Jin J (2015) Contribution of the North Atlantic subtropical high to regional climate model (RCM) skill in simulating southeastern United States summer precipitation. Clim Dyn 45:477–491.  https://doi.org/10.1007/s00382-014-2352-9 CrossRefGoogle Scholar
  23. Liu Y, Wu G (2004) Progress in the study on the formation of the summertime subtropical anticyclone. Adv Atmos Sci 21:322–342.  https://doi.org/10.1007/BF02915562 CrossRefGoogle Scholar
  24. Meehl GA, Tebaldi C (2004) More intense, more frequent, and longer lasting heat waves in the 21st century. Science 305:994–997.  https://doi.org/10.1126/science.1098704 CrossRefGoogle Scholar
  25. Minnesota Department of Health (2015) Heat-related illness weather. https://data.web.health.state.mn.us/hot_weather. Accessed 27 Jun 2018
  26. National Weather Service (2017) 78-year list of severe weather fatalities. http://www.nws.noaa.gov/om/hazstats/resources/weather_fatalities.pdf. Accessed 27 Jun 2018
  27. Nigam S, Chan SC (2009) On the summertime strengthening of the Northern Hemisphere Pacific sea level pressure anticyclone. J Clim 22:1174–1192.  https://doi.org/10.1175/2008JCLI2322.1 CrossRefGoogle Scholar
  28. Peterson TC, Heim RR, Hirsch R et al (2013) Monitoring and understanding changes in heat waves, cold waves, floods, and droughts in the United States: state of knowledge. Bull Am Meteorol Soc 94:821–834.  https://doi.org/10.1175/BAMS-D-12-00066.1 CrossRefGoogle Scholar
  29. Quinlan FT, Karl TR, Williams CN Jr (1987) United States Historical Climatology Network (HCN) Serial Temperature and Precipitation Data. NDP-019. Carbon Dioxide Information Analysis Center. Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, TennesseeGoogle Scholar
  30. Rossow WB, Schiffer RA (1991) ISCCP cloud data products. Bull Am Meteorol Soc 72:2–20.  https://doi.org/10.1175/1520-0477(1991)072%3C0002:ICDP%3E2.0.CO;2 CrossRefGoogle Scholar
  31. Russo S, Sillmann J, Sterl A (2017) Humid heat waves at different warming levels. Sci Rep 7:7477.  https://doi.org/10.1038/s41598-017-07536-7 CrossRefGoogle Scholar
  32. Smith TT, Zaitchik BF, Gohlke JM (2013) Heat waves in the United States: definitions, patterns and trends. Clim Change 118:811–825.  https://doi.org/10.1007/s10584-012-0659-2 CrossRefGoogle Scholar
  33. Stahle DW, Cleaveland MK (1992) Reconstruction and analysis of spring rainfall over the Southeastern US for the past 1000 years. Bull Am Meteorol Soc 73:1947–1961.  https://doi.org/10.1175/1520-0477(1992)073%3C1947:RAAOSR%3E2.0.CO;2 CrossRefGoogle Scholar
  34. Steadman RG (1979) The assessment of sultriness. Part I: a temperature-humidity index based on human physiology and clothing science. J Appl Meteorol 18:861–873.  https://doi.org/10.1175/1520-0450(1979)018%3C0861:TAOSPI%3E2.0.CO;2 CrossRefGoogle Scholar
  35. Taylor KE, Stouffer RJ, Meehl GA et al (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498.  https://doi.org/10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  36. Ting M, Wang H (1997) Summertime US precipitation variability and its relation to Pacific sea surface temperature. J Clim 10:1853–1873.  https://doi.org/10.1175/1520-0442(1997)010%3C1853:SUSPVA%3E2.0.CO;2 CrossRefGoogle Scholar
  37. Trenberth KE, Shea DJ (2005) Relationships between precipitation and surface temperature. Geophys Res Lett.  https://doi.org/10.1029/2005GL022760 Google Scholar
  38. Vanos JK, Kalkstein LS, Sanford TJ (2015) Detecting synoptic warming trends across the US Midwest and implications to human health and heat-related mortality. Int J Climatol 35:85–96.  https://doi.org/10.1002/joc.3964 CrossRefGoogle Scholar
  39. Wallace JM, Hobbs PV (2006) Atmospheric science: an introductory survey, 2nd ed. Academic Press, BurlingtonGoogle Scholar
  40. Wei W, Li W, Deng Y et al (2018a) Dynamical and thermodynamical coupling between the North Atlantic subtropical high and the marine boundary layer clouds in boreal summer. Clim Dyn 50:2457–2469.  https://doi.org/10.1007/s00382-017-3750-6 CrossRefGoogle Scholar
  41. Wei W, Li W, Deng Y, Yang S (2018b) Intraseasonal variation of the summer rainfall over the Southeastern United States. Clim Dyn.  https://doi.org/10.1007/s00382-017-3750-6 Google Scholar
  42. Westcott NE (2011) The prolonged 1954 midwestern US heat wave: impacts and responses. Weather Clim Soc 3:165–176.  https://doi.org/10.1175/WCAS-D-10-05002.1 CrossRefGoogle Scholar
  43. Whitman S, Good G, Donoghue ER et al (1997) Mortality in Chicago attributed to the July 1995 heat wave. Am J Public Health 87:1515–1518CrossRefGoogle Scholar
  44. Wuebbles D, Meehl G, Hayhoe K et al (2013) CMIP5 climate model analyses: climate extremes in the United States. Bull Am Meteorol Soc 95:571–583.  https://doi.org/10.1175/BAMS-D-12-00172.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Earth and Ocean Sciences, Nicholas School of the EnvironmentDuke UniversityDurhamUSA
  2. 2.Department of Atmospheric and Oceanic Sciences, School of PhysicsPeking UniversityBeijingChina
  3. 3.School of Earth and Atmospheric SciencesGeorgia Institute of TechnologyAtlantaUSA
  4. 4.John Dewey AcademyGreat BarringtonUSA
  5. 5.RTI Health SolutionsResearch Triangle ParkUSA
  6. 6.Institute for Health, Health Care Policy and Aging ResearchRutgers Biomedical and Health SciencesNew BrunswickUSA

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