Climatic Change

, Volume 113, Issue 3–4, pp 1001–1024

Climate change: a new metric to measure changes in the frequency of extreme temperatures using record data



Consensus on global warming is the result of multiple and varying lines of evidence, and one key ramification is the increase in frequency of extreme climate events including record high temperatures. Here we develop a metric—called “record equivalent draws” (RED)—based on record high (low) temperature observations, and show that changes in RED approximate changes in the likelihood of extreme high (low) temperatures. Since we also show that this metric is independent of the specifics of the underlying temperature distributions, RED estimates can be aggregated across different climates to provide a genuinely global assessment of climate change. Using data on monthly average temperatures across the global landmass we find that the frequency of extreme high temperatures increased 10-fold between the first three decades of the last century (1900–1929) and the most recent decade (1999–2008). A more disaggregated analysis shows that the increase in frequency of extreme high temperatures is greater in the tropics than in higher latitudes, a pattern that is not indicated by changes in mean temperature. Our RED estimates also suggest concurrent increases in the frequency of both extreme high and extreme low temperatures during 2002–2008, a period when we observe a plateauing of global mean temperature. Using daily extreme temperature observations, we find that the frequency of extreme high temperatures is greater in the daily minimum temperature time-series compared to the daily maximum temperature time-series. There is no such observable difference in the frequency of extreme low temperatures between the daily minimum and daily maximum.

Supplementary material

10584_2011_370_MOESM1_ESM.doc (27 kb)
(DOC 27.0 KB)
10584_2011_370_MOESM2_ESM.pdf (15 kb)
(PDF 14.7 KB)


  1. Alexander LV et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. doi:10.1029/2005JD006290 CrossRefGoogle Scholar
  2. Arnold BC, Balakrishnan N, Nagaraja HN (1998) Records. John Wiley, New YorkCrossRefGoogle Scholar
  3. Ballerini R, Resnick SI (1985) Records from improving populations. J Appl Probab 22:487–502CrossRefGoogle Scholar
  4. Battisti DS, Naylor RL (2009) Historical warnings of future food insecurity with unprecedented seasonal heat. Science 323:240–244CrossRefGoogle Scholar
  5. Benestad RE (2003) How often can we expect a record event? Clim Res 25:3–13CrossRefGoogle Scholar
  6. Bonsal BR, Zhang X, Vincent LA, Hogg WD (2001) Characteristics of daily and extreme temperatures over Canada. J Climate 14:1959–1976CrossRefGoogle Scholar
  7. Breusch TS, Pagan AR (1979) A simple test for heteroskedasticity and random coefficient variation. Econometrica 47:1287–1294CrossRefGoogle Scholar
  8. Brohan P, Kennedy JJ, Harris I, Tett SFB, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850. J Geophys Res 111:D12106. doi:10.1029/2005JD006548 CrossRefGoogle Scholar
  9. Caesar J, Alexander L, Vose R (2006) Large-scale changes in observed daily maximum and minimum temperatures: Creation and analysis of a new gridded data set. J Geophys Res 111:D05101. doi:10.1029/2005JD006280 CrossRefGoogle Scholar
  10. Chandler KN (1952) The distribution and frequency of record values. J Royal Stat Soc B 14:220–228Google Scholar
  11. Choi G et al (2009) Changes in means and extreme events of temperature and precipitation in the Asia-Pacific network region: 1955–2007. Int J Climatol 29:1906–1925CrossRefGoogle Scholar
  12. Ciais Ph et al (2005) Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437:529–533CrossRefGoogle Scholar
  13. Cochrane D, Orcutt GH (1949) Application of least squares regression to relationships containing auto-correlated error terms. J Am Stat Assoc 44:32–61Google Scholar
  14. Curriero FC, Heiner K, Zeger S, Samet JM, Patz JA (2002) Temperature and mortality in 11 cities of the eastern United States. Am J Epidemiol 155:80–87CrossRefGoogle Scholar
  15. Easterling DR et al (1997) Maximum and minimum temperature trends for the globe. Science 277:364–367CrossRefGoogle Scholar
  16. Easterling DR et al (2000) Climate extremes: observations, modeling, and impacts. Science 289:2068–2074CrossRefGoogle Scholar
  17. Frich P et al (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19:193–212CrossRefGoogle Scholar
  18. Githeko AK, Ndegwa W (2001) Predicting malaria epidemics in the Kenyan Highlands using climate data: a tool for decision makers. Glob Change Hum Health 2:54–63CrossRefGoogle Scholar
  19. Gordon AH (1992) Interhemispheric contrasts of mean global temperature anomalies. Int J Climatol 12:1–9CrossRefGoogle Scholar
  20. Griffiths GM et al. (2005) Change in mean temperature as a predictor of extreme temperature change in the Asia–Pacific region. Int J Climatol 25:1301–1330CrossRefGoogle Scholar
  21. Gumbel EJ (1958) Statistics of extremes. Columbia University Press, New YorkGoogle Scholar
  22. Hall P, Tajvidi N (2000) Nonparametric analysis of temporal trend when fitting parametric models to extreme-value data. Stat Sci 15:153–167CrossRefGoogle Scholar
  23. Hay SI et al (2002) Climate change and the resurgence of malaria in the East African highlands. Nature 415:905–909CrossRefGoogle Scholar
  24. Hunter DE, Schwartz SE, Wagener R, Benkovitz CM (1993) Seasonal, latitudinal, and secular variations in temperature trend: evidence for influence of anthropogenic sulfate. Geophys Res Lett 20:2455–2458CrossRefGoogle Scholar
  25. Jones PD, Briffa KR (1992) Global surface air temperature variations during the twentieth century: part 1, spatial, temporal and seasonal details. Holocene 2:165–179Google Scholar
  26. Jones PD et al (1999) Surface air temperature and its changes over the past 150 years. Rev Geophys 37:173–199CrossRefGoogle Scholar
  27. Karl TR, Kukla G, Gavin J (1984) Decreasing diurnal temperature range in the United States and Canada from 1941 through 1980. J Clim Appl Meteorol 23:1489–1504CrossRefGoogle Scholar
  28. Karl TR et al (1991) Global warming: evidence for asymmetric diurnal temperature change. Geophys Res Lett 18:2253–2256CrossRefGoogle Scholar
  29. Karl TR et al (1993) Asymmetric trends of daily maximum and minimum temperature. B Am Meteorol Soc 74:1007–1023CrossRefGoogle Scholar
  30. Kharin VV, Zwiers FW (2000) Changes in the extremes in an ensemble of transient climate simulations with a coupled atmosphere-ocean GCM. J Climate 13:3760–3788CrossRefGoogle Scholar
  31. Kiktev D, Sexton D, Alexander L, Folland C (2003) Comparison of modelled and observed trends in indicators of daily climate extremes. J Climate 16:3560–3571CrossRefGoogle Scholar
  32. Kumar RK, Kumar KK, Pant GB (1994) Diurnal asymmetry of surface temperature trends over India. Geophys Res Lett 21:677–680CrossRefGoogle Scholar
  33. Laurent C, Parey S (2007) Estimation of 100-year-return-period temperatures in France in a non-stationary climate: Results from observations and IPCC scenarios. Glob Planet Change 57:177–188CrossRefGoogle Scholar
  34. Lean JL, Rind DH (2008) How natural and anthropogenic influences alter global and regional surface temperatures: 1889 to 2006. Geophys Res Lett 35: L18701. doi:10.1029/2008GL034864 CrossRefGoogle Scholar
  35. Lean JL, Rind DH (2009) How will Earth’s surface temperature change in future decades? Geophys Res Lett 36:L15708. doi:10.1029/2009GL038932 CrossRefGoogle Scholar
  36. Lund R, Reeves J (2002) Detection of undocumented changepoints: a revision of the two-phase regression model. J Climate 15:2547–2554CrossRefGoogle Scholar
  37. Lund R, Seymour, L, Kafadar K (2001) Temperature trends in the United States. Environmetrics 12:673–690CrossRefGoogle Scholar
  38. Meehl GA, Tebaldi C, Walton G, Easterling D, McDaniel L (2009) Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S. Geophys Res Lett 36:L23701. doi:10.1029/2009GL040736 CrossRefGoogle Scholar
  39. Munasinghe L, O’Flaherty B, Danninger S (2001) Globalization and the rate of technological progress: what track and field records show. J Polit Econ 109:1132–1149CrossRefGoogle Scholar
  40. Nevzorov VB (1985) Record and interrecord times for sequences of nonidentically distributed random variables. J Math Sci 36:510–516. doi:10.1007/BF01663462 CrossRefGoogle Scholar
  41. Nogaj M, Yiou P, Parey S, Malek F, Naveau P (2006) Amplitude and frequency of temperature extremes over the North Atlantic region. Geophys Res Lett 33:L10801. doi:10.1029/2005GL024251 CrossRefGoogle Scholar
  42. Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37–42CrossRefGoogle Scholar
  43. Peterson TC (2005) Climate change indices. WMO Bulletin 54:83–86Google Scholar
  44. Rényi A (1962) Theorie des elements saillants d’une suite d’observations. Colloquium on Combinatorial Methods in Probability Theory, pp 104–117Google Scholar
  45. Rittenhouse CD et al (2010) Avifauna response to hurricanes: regional changes in community similarity. Glob Change Biol 16:905–917CrossRefGoogle Scholar
  46. Rosenzweig C et al (2008) Attributing physical and biological impacts to anthropogenic climate change. Nature 453:353–357CrossRefGoogle Scholar
  47. Schäl C et al (2004) The role of increasing temperature variability in European summer heatwaves. Nature 427:332–336CrossRefGoogle Scholar
  48. Thibault KM, Brown JH (2008) Impact of an extreme climatic event on community assembly. Proc Natl Acad Sci USA 105:3410–3415CrossRefGoogle Scholar
  49. Trenberth KE et al (2007) Observations: surface and atmospheric climate change. In: Solomon et al (eds) Climate change 2007: the physical science. Cambridge University Press, New YorkGoogle Scholar
  50. Walther GR et al (2002) Ecological responses to recent climate change. Nature 416:389–395CrossRefGoogle Scholar
  51. Wang XL, Swail VR (2001) Changes of extreme wave heights in northern hemisphere oceans and related atmospheric circulation regimes. J Climate 14:2204–2221CrossRefGoogle Scholar
  52. Weber RO, Talkner P, Stefanicki G (1994) Asymmetric diurnal temperature change in the Alpine Region. Geophys Res Lett 21:673–676CrossRefGoogle Scholar
  53. Willmott CJ, Matsuura K (1995) Smart interpolation of annually averaged air temperature in the United States. J Appl Meteorol 34:2577–2586CrossRefGoogle Scholar
  54. Yan Z (2002) Trends of extreme temperatures in Europe and China based on daily observations. Clim Change 53:355–392CrossRefGoogle Scholar
  55. Yang MCK (1975) On the distribution of the inter-record times in an increasing population. J Appl Probab 12:148–154CrossRefGoogle Scholar
  56. Yiou P, Goubanova K, Li ZX, Nogaj M (2008) Weather regime dependence of extreme value statistics for summer temperature and precipitation. Nonlinear Process Geophys 15:365–378CrossRefGoogle Scholar
  57. Zhang X, Vincent LA, Hogg WD, Niitsoo A (2000) Temperature and precipitation trends in canada during the 20th century. Atmos Ocean 38:395–429CrossRefGoogle Scholar
  58. Zhang X, Zwiers FW (2004) Comment on “Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test” by Yue S, Wang CY. Water Resour Res 40. doi:10.1029/2003WR002073
  59. Zwiers FW, Kharin VV (1998) Changes in the extremes of the climate simulated by CCC GCM2 under CO2 doubling. J Climate 11:2200–2222CrossRefGoogle Scholar
  60. Zwiers FW, Zhang X, Feng J (2011) Anthropogenic influence on long return period daily temperature extremes at regional scales. J Climate 24:881–892CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Lalith Munasinghe
    • 1
  • Tackseung Jun
    • 2
  • David H. Rind
    • 3
  1. 1.Department of Economics, Barnard CollegeColumbia UniversityNew YorkUSA
  2. 2.Department of EconomicsKyung Hee UniversitySeoulKorea
  3. 3.NASA Goddard Institute for Space StudiesNew YorkUSA

Personalised recommendations