Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

The effects of climate change on hailstorms

Nature Reviews Earth & Environment volume 2, pages 213–226 (2021)Cite this article

Subjects

Abstract

Hailstorms are dangerous and costly phenomena that are expected to change in response to a warming climate. In this Review, we summarize current knowledge of climate change effects on hailstorms. As a result of anthropogenic warming, it is generally anticipated that low-level moisture and convective instability will increase, raising hailstorm likelihood and enabling the formation of larger hailstones; the melting height will rise, enhancing hail melt and increasing the average size of surviving hailstones; and vertical wind shear will decrease overall, with limited influence on the overall hailstorm activity, owing to a predominance of other factors. Given geographic differences and offsetting interactions in these projected environmental changes, there is spatial heterogeneity in hailstorm responses. Observations and modelling lead to the general expectation that hailstorm frequency will increase in Australia and Europe, but decrease in East Asia and North America, while hail severity will increase in most regions. However, these projected changes show marked spatial and temporal variability. Owing to a dearth of long-term observations, as well as incomplete process understanding and limited convection-permitting modelling studies, current and future climate change effects on hailstorms remain highly uncertain. Future studies should focus on detailed processes and account for non-stationarities in proxy relationships.

Key points

  • Efforts to understand the effects of climate change on hail are complicated by the small scale and relative rarity of hailstorms, which make hail hard to observe and model.

  • Climate change affects low-level moisture and convective instability, microphysical processes and vertical wind shear, all of which are relevant to hail formation and properties.

  • A scarcity of hail observations and high-resolution modelling studies, and gaps in the understanding of physical processes, contribute to the current high uncertainty around the effects of climate change on hailstorms worldwide.

  • General indications based on observations and modelling are of overall hailstorm frequency increasing in Australia, slightly increasing in Europe and decreasing in East Asia and the USA.

  • In most regions, hailstorm severity is expected to increase with climate change.

  • Long-term observations and high-resolution modelling are crucial to understanding the effects of climate change on hailstorms. Future studies should focus on furthering process understanding and improving proxy relationships.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Hail-relevant atmospheric phenomena in current and future climates.
Fig. 2: Global hail probability.
Fig. 3: Overview of past-trend studies and their conclusions on hail-frequency trends.
Fig. 4: Overview of future simulation studies and their conclusions on hail-frequency trends.

Similar content being viewed by others

References

  1. World Meteorological Organization (WMO). International Cloud Atlas: Manual on the Observation of Clouds and Other Meteors (WMO-No. 407). World Meteorological Organization (WMO) https://cloudatlas.wmo.int/ (2017).

  2. Knight, C. A. & Knight, N. C. in Severe Convective Storms (ed. Doswell, C. A.) 223–254 (American Meteorological Society, 2001).

  3. Rasmussen, R. M. & Heymsfield, A. J. Melting and shedding of graupel and hail. Part II: sensitivity study. J. Atmos. Sci. 44, 2764–2782 (1987).

    Article  Google Scholar 

  4. Allen, J. T. in Oxford Research Encyclopedia of Climate Science 67 pp (Oxford Univ. Press, 2018).

  5. Kunz, M. et al. The severe hailstorm in southwest Germany on 28 July 2013: characteristics, impacts and meteorological conditions. Q. J. R. Meteorol. Soc. 144, 231–250 (2018).

    Article  Google Scholar 

  6. Allen, J. T. et al. Understanding hail in the earth system. Rev. Geophys. 58, e2019RG000665 (2020).

    Article  Google Scholar 

  7. Púčik, T. et al. Large hail incidence and its economic and societal impacts across Europe. Mon. Weather Rev. 147, 3901–3916 (2019).

    Article  Google Scholar 

  8. Willemse, S. A statistical analysis and climatological interpretation of hailstorms in Switzerland. Thesis, ETH Zürich (1995).

  9. Carver, A. R. et al. Weather radar data correlate to hail-induced mortality in grassland birds. Remote Sens. Ecol. Conserv. 3, 90–101 (2017).

    Article  Google Scholar 

  10. Brooks, H. E. & Dotzek, N. in Climate Extremes and Society (eds Diaz, H. F. & Murnane, R. J.) 35–53 (Cambridge Univ. Press, 2008).

  11. Changnon, S. A. Increasing major hail losses in the US. Clim. Change 96, 161–166 (2009).

    Article  Google Scholar 

  12. Allen, J. T. et al. An extreme value model for US hail size. Mon. Weather Rev. 145, 4501–4519 (2017).

    Article  Google Scholar 

  13. Allen, J. T. & Allen, E. R. A review of severe thunderstorms in Australia. Atmos. Res. 178-179, 347–366 (2016).

    Article  Google Scholar 

  14. Trapp, R. J. et al. Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing. Proc. Natl Acad. Sci. USA 104, 19719–19723 (2007).

    Article  Google Scholar 

  15. Trapp, R. J., Diffenbaugh, N. S. & Gluhovsky, A. Transient response of severe thunderstorm forcing to elevated greenhouse gas concentrations. Geophys. Res. Lett. 36, L01703 (2009).

    Article  Google Scholar 

  16. Brooks, H. E. Severe thunderstorms and climate change. Atmos. Res. 123, 129–138 (2013).

    Article  Google Scholar 

  17. Diffenbaugh, N. S., Scherer, M. & Trapp, R. J. Robust increases in severe thunderstorm environments in response to greenhouse forcing. Proc. Natl Acad. Sci. USA 110, 16361–16366 (2013).

    Article  Google Scholar 

  18. Hoogewind, K. A., Baldwin, M. E. & Trapp, R. J. The impact of climate change on hazardous convective weather in the United States: insight from high-resolution dynamical downscaling. J. Clim. 30, 10081–10100 (2017).

    Article  Google Scholar 

  19. Rasmussen, K. L., Prein, A. F., Rasmussen, R. M., Ikeda, K. & Liu, C. Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States. Clim. Dyn. 55, 383–408 (2017).

    Article  Google Scholar 

  20. Xie, B., Zhang, Q. & Wang, Y. Trends in hail in China during 1960–2005. Geophys. Res. Lett. 35, L13801 (2008).

    Article  Google Scholar 

  21. Mahoney, K., Alexander, M. A., Thompson, G., Barsugli, J. J. & Scott, J. D. Changes in hail and flood risk in high-resolution simulations over Colorado’s mountains. Nat. Clim. Change 2, 125–131 (2012).

    Article  Google Scholar 

  22. Brimelow, J. C., Burrows, W. R. & Hanesiak, J. M. The changing hail threat over North America in response to anthropogenic climate change. Nat. Clim. Change 7, 516–523 (2017).

    Article  Google Scholar 

  23. Prein, A. F. & Heymsfield, A. J. Increased melting level height impacts surface precipitation phase and intensity. Nat. Clim. Change 10, 771–776 (2020).

    Article  Google Scholar 

  24. Kunz, M., Sander, J. & Kottmeier, C. Recent trends of thunderstorm and hailstorm frequency and their relation to atmospheric characteristics in southwest Germany. Int. J. Climatol. 29, 2283–2297 (2009).

    Article  Google Scholar 

  25. Mohr, S. & Kunz, M. Recent trends and variabilities of convective parameters relevant for hail events in Germany and Europe. Atmos. Res. 123, 211–228 (2013).

    Article  Google Scholar 

  26. Madonna, E., Ginsbourger, D. & Martius, O. A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables. Atmos. Res. 203, 261–274 (2018).

    Article  Google Scholar 

  27. Rädler, A. T., Groenemeijer, P., Faust, E. & Sausen, R. Detecting severe weather trends using an additive regressive convective hazard model (AR-CHaMo). J. Appl. Meteorol. Climatol. 57, 569–587 (2018).

    Article  Google Scholar 

  28. Trapp, R. J., Hoogewind, K. A. & Lasher-Trapp, S. Future changes in hail occurrence in the United States determined through convection-permitting dynamical downscaling. J. Clim. 32, 5493–5509 (2019).

    Article  Google Scholar 

  29. Dessens, J., Berthet, C. & Sanchez, J. L. Change in hailstone size distributions with an increase in the melting level height. Atmos. Res. 158-159, 245–253 (2015).

    Article  Google Scholar 

  30. Weisman, M. L. & Klemp, J. B. The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Weather Rev. 112, 2479–2498 (1984).

    Article  Google Scholar 

  31. Dennis, E. J. & Kumjian, M. R. The impact of vertical wind shear on hail growth in simulated supercells. J. Atmos. Sci. 74, 641–663 (2017).

    Article  Google Scholar 

  32. Intergovernmental Panel on Climate Change (IPCC). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (Cambridge Univ. Press, 2012).

  33. Collins, M. et al. in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  34. Hartmann, D. L. et al. in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  35. Tippett, M. K., Allen, J. T., Gensini, V. A. & Brooks, H. E. Climate and hazardous convective weather. Curr. Clim. Change Rep. 1, 60–73 (2015).

    Article  Google Scholar 

  36. Martius, O. et al. Challenges and recent advances in hail research. Bull. Am. Meteorol. Soc. 99, ES51–ES54 (2018).

    Article  Google Scholar 

  37. Pruppacher, H. R. & Klett, J. D. Microphysics of Clouds and Precipitation 2nd edn Vol. 18 (Springer, 2010).

  38. Wallace, J. M. & Hobbs, P. V. Atmospheric Science: an Introductory Survey 2nd edn Vol. 92 (Elsevier, 2006).

  39. Brimelow, J. in Oxford Research Encyclopedia of Climate Science (Oxford Univ. Press, 2018).

  40. Browning, K. A. et al. The convective storm initiation project. Bull. Am. Meteorol. Soc. 88, 1939–1956 (2007).

    Article  Google Scholar 

  41. Kottmeier, C. et al. Mechanisms initiating deep convection over complex terrain during COPS. Meteorol. Z. 17, 931–948 (2008).

    Article  Google Scholar 

  42. Carlson, T. N., Benjamin, S. G., Forbes, G. S. & Li, Y.-F. Elevated mixed layers in the regional severe storm environment: conceptual model and case studies. Mon. Weather Rev. 111, 1453–1474 (1983).

    Article  Google Scholar 

  43. Doswell, C. A., Brooks, H. E. & Maddox, R. A. Flash flood forecasting: an ingredients-based methodology. Weather Forecast. 11, 560–581 (1996).

    Article  Google Scholar 

  44. Morgan, G. M. Jr. An examination of the wet-bulb zero as a hail forecasting parameter in the Po Valley, Italy. J. Appl. Meteorol. 9, 537–540 (1970).

    Article  Google Scholar 

  45. Vali, G., DeMott, P. J., Möhler, O. & Whale, T. F. Technical note: a proposal for ice nucleation terminology. Atmos. Chem. Phys. 15, 10263–10270 (2015).

    Article  Google Scholar 

  46. Knight, C. A. & Knight, N. C. Hailstone embryos. J. Atmos. Sci. 27, 659–666 (1970).

    Article  Google Scholar 

  47. Brimelow, J. C., Reuter, G. W. & Poolman, E. R. Modeling maximum hail size in Alberta thunderstorms. Weather Forecast. 17, 1048–1062 (2002).

    Article  Google Scholar 

  48. Eccel, E., Cau, P., Riemann-Campe, K. & Biasioli, F. Quantitative hail monitoring in an alpine area: 35-year climatology and links with atmospheric variables. Int. J. Climatol. 32, 503–517 (2012).

    Article  Google Scholar 

  49. Foote, G. B. A study of hail growth utilizing observed storm conditions. J. Clim. Appl. Meteorol. 23, 84–101 (1984).

    Article  Google Scholar 

  50. Nelson, S. P. The hybrid multicellular–supercellular storm — an efficient hail producer. Part II. General characteristics and implications for hail growth. J. Atmos. Sci. 44, 2060–2073 (1987).

    Article  Google Scholar 

  51. Xie, B., Zhang, Q. & Wang, Y. Observed characteristics of hail size in four regions in China during 1980–2005. J. Clim. 23, 4973–4982 (2010).

    Article  Google Scholar 

  52. Nelson, S. P. The influence of storm flow structure on hail growth. J. Atmos. Sci. 40, 1965–1983 (1983).

    Article  Google Scholar 

  53. Kumjian, M. R., Lebo, Z. J. & Ward, A. M. Storms producing large accumulations of small hail. J. Appl. Meteorol. Climatol. 58, 341–364 (2019).

    Article  Google Scholar 

  54. Blair, S. F. et al. High-resolution hail observations: implications for NWS warning operations. Weather Forecast. 32, 1101–1119 (2017).

    Article  Google Scholar 

  55. Bruick, Z. S., Rasmussen, K. L. & Cecil, D. J. Subtropical South American hailstorm characteristics and environments. Mon. Weather Rev. 147, 4289–4304 (2019).

    Article  Google Scholar 

  56. Allen, J. T. & Karoly, D. J. A climatology of Australian severe thunderstorm environments 1979–2011: inter-annual variability and ENSO influence. Int. J. Climatol. 34, 81–97 (2014).

    Article  Google Scholar 

  57. Seeley, J. T. & Romps, D. M. The effect of global warming on severe thunderstorms in the United States. J. Clim. 28, 2443–2458 (2015).

    Article  Google Scholar 

  58. Wellmann, C. et al. Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail. Atmos. Chem. Phys. 20, 2201–2219 (2020).

    Article  Google Scholar 

  59. Brooks, H. E., Lee, J. W. & Craven, J. P. The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data. Atmos. Res. 67-68, 73–94 (2003).

    Article  Google Scholar 

  60. Allen, J. T., Karoly, D. J. & Mills, G. A. A severe thunderstorm climatology for Australia and associated thunderstorm environments. Aust. Meteorol. Oceanogr. J. 61, 143–158 (2011).

    Article  Google Scholar 

  61. Fraile, R., Castro, A., López, L., Sánchez, J. L. & Palencia, C. The influence of melting on hailstone size distribution. Atmos. Res. 67-68, 203–213 (2003).

    Article  Google Scholar 

  62. Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 5686–5699 (2006).

    Article  Google Scholar 

  63. Rädler, A. T., Groenemeijer, P. H., Faust, E., Sausen, R. & Púčik, T. Frequency of severe thunderstorms across Europe expected to increase in the 21st century due to rising instability. NPJ Clim. Atmos. Sci. 2, 30 (2019).

    Article  Google Scholar 

  64. Gensini, V. A., Ramseyer, C. & Mote, T. L. Future convective environments using NARCCAP. Int. J. Climatol. 34, 1699–1705 (2014).

    Article  Google Scholar 

  65. Allen, J. T., Karoly, D. J. & Walsh, K. J. Future Australian severe thunderstorm environments. Part II: the influence of a strongly warming climate on convective environments. J. Clim. 27, 3848–3868 (2014).

    Article  Google Scholar 

  66. Chen, J., Dai, A., Zhang, Y. & Rasmussen, K. L. Changes in convective available potential energy and convective inhibition under global warming. J. Clim. 33, 2025–2050 (2020).

    Article  Google Scholar 

  67. Marsh, P. T., Brooks, H. E. & Karoly, D. J. Preliminary investigation into the severe thunderstorm environment of Europe simulated by the Community Climate System Model 3. Atmos. Res. 93, 607–618 (2009).

    Article  Google Scholar 

  68. Crook, N. A. Sensitivity of moist convection forced by boundary layer processes to low-level thermodynamic fields. Mon. Weather Rev. 124, 1767–1785 (1996).

    Article  Google Scholar 

  69. Brimelow, J. C., Reuter, G. W., Goodson, R. & Krauss, T. W. Spatial forecasts of maximum hail size using prognostic model soundings and HAILCAST. Weather Forecast. 21, 206–219 (2006).

    Article  Google Scholar 

  70. Giaiotti, D. B. & Stel, F. The effects of environmental water vapor on hailstone size distributions. Atmos. Res. 82, 455–462 (2006).

    Article  Google Scholar 

  71. Jewell, R. & Brimelow, J. Evaluation of Alberta hail growth model using severe hail proximity soundings from the United States. Weather Forecast. 24, 1592–1609 (2009).

    Article  Google Scholar 

  72. Li, M., Zhang, F., Zhang, Q., Harrington, J. Y. & Kumjian, M. R. Nonlinear response of hail precipitation rate to environmental moisture content: a real case modeling study of an episodic midlatitude severe convective event. J. Geophys. Res. Atmos. 122, 6729–6747 (2017).

    Article  Google Scholar 

  73. Trapp, R. J. & Hoogewind, K. A. The realization of extreme tornadic storm events under future anthropogenic climate change. J. Clim. 29, 5251–5265 (2016).

    Article  Google Scholar 

  74. Li, M., Zhang, Q. & Zhang, F. Hail day frequency trends and associated atmospheric circulation patterns over China during 1960–2012. J. Clim. 29, 7027–7044 (2016).

    Article  Google Scholar 

  75. Taszarek, M., Allen, J. T., Brooks, H. E., Pilguj, N. & Czernecki, B. Differing trends in United States and European severe thunderstorm environments in a warming climate. Bull. Am. Meteorol. Soc. https://doi.org/10.1175/BAMS-D-20-0004.1 (2020).

    Article  Google Scholar 

  76. McMaster, H. J. The potential impact of global warming on hail losses to winter cereal crops in New South Wales. Clim. Change 43, 455–476 (1999).

    Article  Google Scholar 

  77. Tang, B. H., Gensini, V. A. & Homeyer, C. R. Trends in United States large hail environments and observations. NPJ Clim. Atmos. Sci. 2, 45 (2019).

    Article  Google Scholar 

  78. Warren, R. A., Richter, H., Ramsay, H. A., Siems, S. T. & Manton, M. J. Impact of variations in upper-level shear on simulated supercells. Mon. Weather Rev. 145, 2659–2681 (2017).

    Article  Google Scholar 

  79. Morrison, H. & Milbrandt, J. A. Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part I: scheme description and idealized tests. J. Atmos. Sci. 72, 287–311 (2015).

    Article  Google Scholar 

  80. DeMott, P. J. et al. Predicting global atmospheric ice nuclei distributions and their impacts on climate. Proc. Natl Acad. Sci. USA 107, 11217–11222 (2010).

    Article  Google Scholar 

  81. Villanueva-Birriel, C. M., Lasher-Trapp, S., Trapp, R. J. & Diffenbaugh, N. Sensitivity of the warm rain process in convective clouds to regional climate change in the contiguous US. J. Clouds Aerosols Radiat. 1, 1–17 (2014).

    Google Scholar 

  82. Zou, T., Zhang, Q., Li, W. & Li, J. Responses of hail and storm days to climate change in the Tibetan Plateau. Geophys. Res. Lett. 45, 4485–4493 (2018).

    Article  Google Scholar 

  83. van den Heever, S. C. & Cotton, W. R. The impact of hail size on simulated supercell storms. J. Atmos. Sci. 61, 1596–1609 (2004).

    Article  Google Scholar 

  84. Cecil, D. J. & Blankenship, C. B. Toward a global climatology of severe hailstorms as estimated by satellite passive microwave imagers. J. Clim. 25, 687–703 (2012).

    Article  Google Scholar 

  85. Prein, A. F. & Holland, G. J. Global estimates of damaging hail hazard. Weather Clim. Extremes 22, 10–23 (2018).

    Article  Google Scholar 

  86. Zhang, C., Zhang, Q. & Wang, Y. Climatology of hail in China: 1961–2005. J. Appl. Meteorol. Climatol. 47, 795–804 (2008).

    Article  Google Scholar 

  87. Zhang, Q., Ni, X. & Zhang, F. Decreasing trend in severe weather occurrence over China during the past 50 years. Sci. Rep. 7, 42310 (2017).

    Article  Google Scholar 

  88. Shi, J., Wen, K. & Cui, L. Patterns and trends of high-impact weather in China during 1959–2014. Nat. Hazards Earth Syst. Sci. 16, 855–869 (2016).

    Article  Google Scholar 

  89. Ni, X. et al. Decreased hail size in China since 1980. Sci. Rep. 7, 10913 (2017).

    Article  Google Scholar 

  90. Ni, X., Muehlbauer, A., Allen, J. T., Zhang, Q. & Fan, J. A climatology and extreme value analysis of large hail in China. Mon. Weather Rev. 148, 1431–1447 (2020).

    Article  Google Scholar 

  91. Wu, M., Chen, Y. & Xu, C. Assessment of meteorological disasters based on information diffusion theory in Xinjiang, Northwest China. J. Geogr. Sci. 25, 69–84 (2015).

    Article  Google Scholar 

  92. Lkhamjav, J., Jin, H.-G., Lee, H. & Baik, J.-J. A hail climatology in Mongolia. Asia-Pac. J. Atmos. Sci. 53, 501–509 (2017).

    Article  Google Scholar 

  93. Jin, H.-G., Lee, H., Lkhamjav, J. & Baik, J.-J. A hail climatology in South Korea. Atmos. Res. 188, 90–99 (2017).

    Article  Google Scholar 

  94. Punge, H. J. & Kunz, M. Hail observations and hailstorm characteristics in Europe: a review. Atmos. Res. 176-177, 159–184 (2016).

    Article  Google Scholar 

  95. Burcea, S., Cică, R. & Bojariu, R. Hail climatology and trends in Romania: 1961–2014. Mon. Weather Rev. 144, 4289–4299 (2016).

    Article  Google Scholar 

  96. Aran, M., Pena, J. C. & Torà, M. Atmospheric circulation patterns associated with hail events in Lleida (Catalonia). Atmos. Res. 100, 428–438 (2011).

    Article  Google Scholar 

  97. Simeonov, P., Bocheva, L. & Marinova, T. Severe convective storms phenomena occurrence during the warm half of the year in Bulgaria (1961–2006). Atmos. Res. 93, 498–505 (2009).

    Article  Google Scholar 

  98. Ćurić, M. & Janc, D. Hail climatology in Serbia. Int. J. Climatol. 36, 3270–3279 (2016).

    Article  Google Scholar 

  99. Kapsch, M. L., Kunz, M., Vitolo, R. & Economou, T. Long-term trends of hail-related weather types in an ensemble of regional climate models using a Bayesian approach. J. Geophys. Res. Atmos. 117, D15107 (2012).

    Article  Google Scholar 

  100. Hohl, R., Schweingruber, F. H. & Schiesser, H.-H. Reconstruction of severe hailstorm occurrence with tree rings: a case study in central Switzerland. Tree-Ring Res. 58, 11–22 (2002).

    Google Scholar 

  101. Nisi, L., Hering, A., Germann, U. & Martius, O. A 15-year hail streak climatology for the Alpine region. Q. J. R. Meteorol. Soc. 144, 1429–1449 (2018).

    Article  Google Scholar 

  102. Groenemeijer, P. et al. Severe convective storms in Europe: ten years of research and education at the European Severe Storms Laboratory. Bull. Am. Meteorol. Soc. 98, 2641–2651 (2017).

    Article  Google Scholar 

  103. Pocakal, D. Hailpad data analysis for the continental part of Croatia. Meteorol. Z. 20, 441–447 (2011).

    Article  Google Scholar 

  104. Dessens, J., Fraile, R., Pont, V. & Sánchez, J. L. Day-of-the-week variability of hail in southwestern France. Atmos. Res. 59-60, 63–76 (2001).

    Article  Google Scholar 

  105. Berthet, C., Dessens, J. & Sanchez, J. L. Regional and yearly variations of hail frequency and intensity in France. Atmos. Res. 100, 391–400 (2011).

    Article  Google Scholar 

  106. Manzato, A. Hail in northeast Italy: climatology and bivariate analysis with the sounding-derived indices. J. Appl. Meteorol. Climatol. 51, 449–467 (2012).

    Article  Google Scholar 

  107. Hermida, L. et al. Climatic trends in hail precipitation in France: spatial, altitudinal, and temporal variability. Sci. World J. 2013, 494971 (2013).

    Article  Google Scholar 

  108. Hermida, L. et al. Hailfall in southwest France: relationship with precipitation, trends and wavelet analysis. Atmos. Res. 156, 174–188 (2015).

    Article  Google Scholar 

  109. Sanchez, J. L. et al. Are meteorological conditions favoring hail precipitation change in southern Europe? Analysis of the period 1948–2015. Atmos. Res. 198, 1–10 (2017).

    Article  Google Scholar 

  110. Dessens, J. Severe convective weather in the context of a nighttime global warming. Geophys. Res. Lett. 22, 1241–1244 (1995).

    Article  Google Scholar 

  111. Botzen, W. J. W., Bouwer, L. M. & van den Bergh, J. C. J. M. Climate change and hailstorm damage: empirical evidence and implications for agriculture and insurance. Resour. Energy Econ. 32, 341–362 (2010).

    Article  Google Scholar 

  112. Mohr, S., Kunz, M. & Keuler, K. Development and application of a logistic model to estimate the past and future hail potential in Germany. J. Geophys. Res. Atmos. 120, 3939–3956 (2015).

    Article  Google Scholar 

  113. Saa Requejo, A., García Moreno, R., Díaz Alvarez, M. C., Burgaz, F. & Tarquis, A. M. Analysis of hail damages and temperature series for peninsular Spain. Nat. Hazards Earth Syst. Sci. 11, 3415–3422 (2011).

    Article  Google Scholar 

  114. Piani, F., Crisci, A., De Chiara, G., Maracchi, G. & Meneguzzo, F. Recent trends and climatic perspectives of hailstorms frequency and intensity in Tuscany and Central Italy. Nat. Hazards Earth Syst. Sci. 5, 217–224 (2005).

    Article  Google Scholar 

  115. García-Ortega, E. et al. Anomalies, trends and variability in atmospheric fields related to hailstorms in north-eastern Spain. Int. J. Climatol. 34, 3251–3263 (2014).

    Article  Google Scholar 

  116. Mohr, S., Kunz, M. & Geyer, B. Hail potential in Europe based on a regional climate model hindcast. Geophys. Res. Lett. 42, 10904–10912 (2015).

    Article  Google Scholar 

  117. Sanderson, M. G. et al. Projected changes in hailstorms during the 21st century over the UK. Int. J. Climatol. 35, 15–24 (2015).

    Article  Google Scholar 

  118. Changnon, S. A. & Changnon, D. Long-term fluctuations in hail incidences in the United States. J. Clim. 13, 658–664 (2000).

    Article  Google Scholar 

  119. Etkin, D. & Brun, S. E. A note on Canada’s hail climatology: 1977–1993. Int. J. Climatol. 19, 1357–1373 (1999).

    Article  Google Scholar 

  120. Cao, Z. Severe hail frequency over Ontario, Canada: recent trend and variability. Geophys. Res. Lett. 35, L14803 (2008).

    Article  Google Scholar 

  121. Allen, J. T. & Tippett, M. K. The characteristics of United States hail reports: 1955-2014. Electron. J. Severe Storms Meteorol. 10, 1–31 (2015).

    Google Scholar 

  122. Barrett, B. S. & Henley, B. N. Intraseasonal variability of hail in the contiguous United States: relationship to the Madden–Julian oscillation. Mon. Weather Rev. 143, 1086–1103 (2015).

    Article  Google Scholar 

  123. Kunkel, K. E., Pielke, R. A. & Changnon, S. A. Temporal fluctuations in weather and climate extremes that cause economic and human health impacts: a review. Bull. Am. Meteorol. Soc. 80, 1077–1098 (1999).

    Article  Google Scholar 

  124. Witt, A. et al. An enhanced hail detection algorithm for the WSR-88D. Weather Forecast. 13, 286–303 (1998).

    Article  Google Scholar 

  125. Schlie, E. E.-J., Wuebbles, D., Stevens, S., Trapp, R. & Jewett, B. A radar-based study of severe hail outbreaks over the contiguous United States for 2000–2011. Int. J. Climatol. 39, 278–291 (2019).

    Article  Google Scholar 

  126. Allen, J. T., Tippett, M. K. & Sobel, A. H. An empirical model relating US monthly hail occurrence to large-scale meteorological environment. J. Adv. Model. Earth Syst. 7, 226–243 (2015).

    Article  Google Scholar 

  127. Childs, S. J., Schumacher, R. S. & Strader, S. M. Projecting end-of-century human exposure from tornadoes and severe hailstorms in eastern Colorado: meteorological and population perspectives. Weather Clim. Soc. 12, 575–595 (2020).

    Article  Google Scholar 

  128. Rasmussen, K. L., Zuluaga, M. D. & Houze, R. A. Jr. Severe convection and lightning in subtropical South America. Geophys. Res. Lett. 41, 7359–7366 (2014).

    Article  Google Scholar 

  129. Mezher, R. N., Doyle, M. & Barros, V. Climatology of hail in Argentina. Atmos. Res. 114-115, 70–82 (2012).

    Article  Google Scholar 

  130. Martins, J. A. et al. Climatology of destructive hailstorms in Brazil. Atmos. Res. 184, 126–138 (2017).

    Article  Google Scholar 

  131. Beal, A. et al. Climatology of hail in the triple border Paraná, Santa Catarina (Brazil) and Argentina. Atmos. Res. 234, 104747 (2020).

    Article  Google Scholar 

  132. Prieto, R. et al. Interannual variability of hail-days in the Andes region since 1885. Earth Planet. Sci. Lett. 171, 503–509 (1999).

    Article  Google Scholar 

  133. Schuster, S. S., Blong, R. J. & Speer, M. S. A hail climatology of the greater Sydney area and New South Wales, Australia. Int. J. Climatol. 25, 1633–1650 (2005).

    Article  Google Scholar 

  134. Rasuly, A. A., Cheung, K. K. W. & McBurney, B. Hail events across the greater metropolitan severe thunderstorm warning area. Nat. Hazards Earth Syst. Sci. 15, 973–984 (2015).

    Article  Google Scholar 

  135. Niall, S. & Walsh, K. The impact of climate change on hailstorms in southeastern Australia. Int. J. Climatol. 25, 1933–1952 (2005).

    Article  Google Scholar 

  136. Leslie, L. M., Leplastrier, M. & Buckley, B. W. Estimating future trends in severe hailstorms over the Sydney Basin: a climate modelling study. Atmos. Res. 87, 37–51 (2008).

    Article  Google Scholar 

  137. Allen, J. T., Karoly, D. J. & Walsh, K. J. Future Australian severe thunderstorm environments. Part I: a novel evaluation and climatology of convective parameters from two climate models for the late twentieth century. J. Clim. 27, 3827–3847 (2014).

    Article  Google Scholar 

  138. Vogel, M. M. et al. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks. Geophys. Res. Lett. 44, 1511–1519 (2017).

    Article  Google Scholar 

  139. Myoung, B. & Nielsen-Gammon, J. W. The convective instability pathway to warm season drought in Texas. Part I: the role of convective inhibition and its modulation by soil moisture. J. Clim. 23, 4461–4473 (2010).

    Article  Google Scholar 

  140. Gagne, D. J. II, Haupt, S. E., Nychka, D. W. & Thompson, G. Interpretable deep learning for spatial analysis of severe hailstorms. Mon. Weather Rev. 147, 2827–2845 (2019).

    Article  Google Scholar 

  141. Lyubchich, V., Newlands, N. K., Ghahari, A., Mahdi, T. & Gel, Y. R. Insurance risk assessment in the face of climate change: integrating data science and statistics. Wiley Interdiscip. Rev. Comput. Stat. 11, e1462 (2019).

    Article  Google Scholar 

  142. Allen, J. T., Tippett, M. K. & Sobel, A. H. Influence of the El Niño/Southern Oscillation on tornado and hail frequency in the United States. Nat. Geosci. 8, 278–283 (2015).

    Article  Google Scholar 

  143. Baggett, C. F. et al. Skillful subseasonal forecasts of weekly tornado and hail activity using the Madden-Julian oscillation. J. Geophys. Res. Atmos. 123, 12661–12675 (2018).

    Article  Google Scholar 

  144. Lepore, C., Tippett, M. K. & Allen, J. T. CFSv2 monthly forecasts of tornado and hail activity. Weather Forecast. 33, 1283–1297 (2018).

    Article  Google Scholar 

  145. Púčik, T., Groenemeijer, P., Rýva, D. & Kolář, M. Proximity soundings of severe and nonsevere thunderstorms in central Europe. Mon. Weather. Rev. 143, 4805–4821 (2015).

    Article  Google Scholar 

  146. Wellmann, C. et al. Using emulators to understand the sensitivity of deep convective clouds and hail to environmental conditions. J. Adv. Model. Earth Syst. 10, 3103–3122 (2018).

    Google Scholar 

  147. Brooks, H. E. Proximity soundings for severe convection for Europe and the United States from reanalysis data. Atmos. Res. 93, 546–553 (2009).

    Article  Google Scholar 

  148. Sánchez, J. L. et al. Crop damage: the hail size factor. J. Appl. Meteorol. 35, 1535–1541 (1996).

    Article  Google Scholar 

  149. Gupta, V., Sharma, M., Pachauri, R. & Babu, K. N. D. Impact of hailstorm on the performance of PV module: a review. Energy Sourc. A Recovery Util. Environ. Effects https://doi.org/10.1080/15567036.2019.1648597 (2019).

    Article  Google Scholar 

  150. Changnon, S. A. Hailstreaks. J. Atmos. Sci. 27, 109–125 (1970).

    Article  Google Scholar 

  151. Nisi, L., Martius, O., Hering, A., Kunz, M. & Germann, U. Spatial and temporal distribution of hailstorms in the Alpine region: a long-term, high resolution, radar-based analysis. Q. J. R. Meteorol. Soc. 142, 1590–1604 (2016).

    Article  Google Scholar 

  152. Kunkel, K. E. et al. Monitoring and understanding trends in extreme storms. Bull. Am. Meteorol. Soc. 94, 499–514 (2013).

    Article  Google Scholar 

  153. Tuovinen, J.-P., Punkka, A.-J., Rauhala, J., Hohti, H. & Schultz, D. M. Climatology of severe hail in Finland: 1930–2006. Mon. Weather Rev. 137, 2238–2249 (2009).

    Article  Google Scholar 

  154. Webb, J. D. C., Elsom, D. M. & Meaden, G. T. Severe hailstorms in Britain and Ireland, a climatological survey and hazard assessment. Atmos. Res. 93, 587–606 (2009).

    Article  Google Scholar 

  155. Kahraman, A., Tilev-Tanriover, Ş., Kadioglu, M., Schultz, D. M. & Markowski, P. M. Severe hail climatology of Turkey. Mon. Weather Rev. 144, 337–346 (2016).

    Article  Google Scholar 

  156. Childs, S. J. & Schumacher, R. S. An updated severe hail and tornado climatology for eastern Colorado. J. Appl. Meteorol. Climatol. 58, 2273–2293 (2019).

    Article  Google Scholar 

  157. Schleusener, R. A. & Jennings, P. C. An energy method for relative estimates of hail intensity. Bull. Am. Meteorol. Soc. 41, 372–376 (1960).

    Article  Google Scholar 

  158. Smith, P. L. & Waldvogel, A. On determinations of maximum hailstone sizes from hailpad observations. J. Appl. Meteorol. 28, 71–76 (1989).

    Article  Google Scholar 

  159. Waldvogel, A., Federer, B. & Grimm, P. Criteria for the detection of hail cells. J. Appl. Meteorol. 18, 1521–1525 (1979).

    Article  Google Scholar 

  160. Kunz, M. & Kugel, P. I. S. Detection of hail signatures from single-polarization C-band radar reflectivity. Atmos. Res. 153, 565–577 (2015).

    Article  Google Scholar 

  161. Punge, H. J., Bedka, K. M., Kunz, M. & Reinbold, A. Hail frequency estimation across Europe based on a combination of overshooting top detections and the ERA-INTERIM reanalysis. Atmos. Res. 198, 34–43 (2017).

    Article  Google Scholar 

  162. Sander, J., Eichner, J. F., Faust, E. & Steuer, M. Rising variability in thunderstorm-related US losses as a reflection of changes in large-scale thunderstorm forcing. Weather Clim. Soc. 5, 317–331 (2013).

    Article  Google Scholar 

  163. Sioutas, M. V. & Flocas, H. A. Hailstorms in Northern Greece: synoptic patterns and thermodynamic environment. Theor. Appl. Climatol. 75, 189–202 (2003).

    Article  Google Scholar 

  164. Počakal, D., Večenaj, Ž. & Štalec, J. Hail characteristics of different regions in continental part of Croatia based on influence of orography. Atmos. Res. 93, 516–525 (2009).

    Article  Google Scholar 

  165. Malkarova, A. M. Estimation of physical efficiency of hail protection accounting for changes in hail climatology. Russ. Meteorol. Hydrol. 36, 392–398 (2011).

    Article  Google Scholar 

  166. Johns, R. H. & Doswell, C. A. Severe local storms forecasting. Weather Forecast. 7, 588–612 (1992).

    Article  Google Scholar 

  167. van Delden, A. The synoptic setting of thunderstorms in western Europe. Atmos. Res. 56, 89–110 (2001).

    Article  Google Scholar 

  168. Adams-Selin, R. D. & Ziegler, C. L. Forecasting hail using a one-dimensional hail growth model within WRF. Mon. Weather. Rev. 144, 4919–4939 (2016).

    Article  Google Scholar 

  169. Done, J., Davis, C. A. & Weisman, M. The next generation of NWP: explicit forecasts of convection using the Weather Research and Forecasting (WRF) model. Atmos. Sci. Lett. 5, 110–117 (2004).

    Article  Google Scholar 

  170. Trapp, R. J., Halvorson, B. A. & Diffenbaugh, N. S. Telescoping, multimodel approaches to evaluate extreme convective weather under future climates. J. Geophys. Res. Atmos. 112, D20109 (2007).

    Article  Google Scholar 

  171. Liu, C. et al. Continental-scale convection-permitting modeling of the current and future climate of North America. Clim. Dyn. 49, 71–95 (2017).

    Article  Google Scholar 

  172. Weisman, M. L., Skamarock, W. C. & Klemp, J. B. The resolution dependence of explicitly modeled convective systems. Mon. Weather Rev. 125, 527–548 (1997).

    Article  Google Scholar 

  173. Bryan, G. H., Wyngaard, J. C. & Fritsch, J. M. Resolution requirements for the simulation of deep moist convection. Mon. Weather Rev. 131, 2394–2416 (2003).

    Article  Google Scholar 

  174. Seifert, A., Köhler, C. & Beheng, K. D. Aerosol-cloud-precipitation effects over Germany as simulated by a convective-scale numerical weather prediction model. Atmos. Chem. Phys. 12, 709–725 (2012).

    Article  Google Scholar 

  175. Gómez-Navarro, J. J. et al. Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events. Clim. Dyn. https://doi.org/10.1007/s00382-019-04818-w (2019).

    Article  Google Scholar 

  176. Hohenegger, C., Brockhaus, P., Bretherton, C. S. & Schär, C. The soil moisture–precipitation feedback in simulations with explicit and parameterized convection. J. Clim. 22, 5003–5020 (2009).

    Article  Google Scholar 

Download references

Acknowledgements

J.T.A. acknowledges support from the US National Science Foundation (grant no. AGS-1945286). T.H.R. acknowledges support from the Australian Research Council (grant no. ARC LF150100035). K.L.R. acknowledges support from the US National Science Foundation (grant no. AGS-1661657). M.K. is funded by the Helmholtz Association. Q.Z. acknowledges support from the Chinese National Science Foundation (grant no. 42030607).

Author information

Author notes

  1. Timothy H. Raupach

    Present address: Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia

Authors and Affiliations

  1. Institute of Geography, University of Bern, Bern, Switzerland

    Timothy H. Raupach & Olivia Martius

  2. Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland

    Timothy H. Raupach & Olivia Martius

  3. Mobiliar Lab for Natural Risks, University of Bern, Bern, Switzerland

    Olivia Martius

  4. Department of Earth and Atmospheric Sciences, Central Michigan University, Mount Pleasant, MI, USA

    John T. Allen

  5. Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Michael Kunz & Susanna Mohr

  6. Center for Disaster Management and Risk Reduction Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Michael Kunz & Susanna Mohr

  7. Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA

    Sonia Lasher-Trapp & Robert J. Trapp

  8. Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA

    Kristen L. Rasmussen

  9. Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China

    Qinghong Zhang

Authors
  1. Timothy H. Raupach
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Olivia Martius
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John T. Allen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael Kunz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sonia Lasher-Trapp
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Susanna Mohr
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kristen L. Rasmussen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Robert J. Trapp
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Qinghong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

O.M. initiated the project and assembled the authorship team. T.H.R. led the project, researched the data and drafted the manuscript and original figures. All authors contributed to writing and editing of the manuscript prior to submission.

Corresponding author

Correspondence to Timothy H. Raupach.

Ethics declarations

Competing interests

T.H.R. (until 31.12.2019) and O.M. (ongoing) were funded by die Mobiliar insurance group. This funding source played no role in any part of this study. The other authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Earth & Environment thanks A. Prein, R. Hallak, J. Brimelow 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.

Related links

Australian Government Bureau of Meteorology Severe Storms Archive: http://www.bom.gov.au/australia/stormarchive/

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Raupach, T.H., Martius, O., Allen, J.T. et al. The effects of climate change on hailstorms. Nat Rev Earth Environ 2, 213–226 (2021). https://doi.org/10.1038/s43017-020-00133-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43017-020-00133-9

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing