Global Increasing Trends in Annual Maximum Daily Precipitation

Seth Westra School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, Australia

Search for other papers by Seth Westra in
Current site
Google Scholar
PubMed
Close
,
Lisa V. Alexander Climate Change Research Centre, Faculty of Science, and Centre of Excellence for Climate System Science, University of New South Wales, Sydney, Australia

Search for other papers by Lisa V. Alexander in
Current site
Google Scholar
PubMed
Close
, and
Francis W. Zwiers Pacific Climate Impacts Consortium, University of Victoria, Victoria, British Columbia, Canada

Search for other papers by Francis W. Zwiers in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann–Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

Corresponding author address: Seth Westra, School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, SA 5005, Australia. E-mail: seth.westra@adelaide.edu.au

Abstract

This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann–Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

Corresponding author address: Seth Westra, School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, SA 5005, Australia. E-mail: seth.westra@adelaide.edu.au
Save
  • Alexander, L. V., and J. M. Arblaster, 2009: Assessing trends in observed and modelled climate extremes over Australia in relation to future projections. Int. J. Climatol., 29, 417435.

    • Search Google Scholar
    • Export Citation
  • Alexander, L. V., and Coauthors, 2006: Global observed changes in daily climatic extremes of temperature and precipitation. J. Geophys. Res., 111, D05101, doi:10.1029/2005JD006290.

    • Search Google Scholar
    • Export Citation
  • Allen, M. R., and W. J. Ingram, 2002: Constraints on future changes in climate and the hydrological cycle. Nature, 419, 224232.

  • Bates, B. C., Z. W. Kundzewicz, S. Wu, and J. P. Palutikof, Eds., 2008: Climate change and water. IPCC Tech. Paper 6, 210 pp. [Available online at http://www.ipcc.ch/pdf/technical-papers/climate-change-water-en.pdf.]

  • Berg, P., J. O. Haerter, P. Thejll, C. Piani, S. Hagemann, and J. H. Christensen, 2009: Seasonal characteristics of the relationship between daily precipitation intensity and surface temperature. J. Geophys. Res., 114, D18102, doi:10.1029/2009JD012008.

    • Search Google Scholar
    • Export Citation
  • Chandler, R. E., and E. M. Scott, 2011: Statistical Methods for Trend Detection and Analysis in the Environmental Sciences. John Wiley & Sons, 368 pp.

  • Coles, S. G., 2001: An Introduction to Statistical Modelling of Extreme Values, Springer, 208 pp.

  • Coles, S. G., L. R. Pericchi, and S. A. Sisson, 2003: A fully probabilistic approach to extreme value modelling. J. Hydrol., 273, 3550.

    • Search Google Scholar
    • Export Citation
  • Donat, M. G., and Coauthors, 2013: Updated analysis of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset. J. Geophys. Res., 118, 20982118, doi:10.1002/jgrd.50150.

    • Search Google Scholar
    • Export Citation
  • Durre, I., M. J. Menne, B. E. Gleason, T. G. Houston, and R. S. Vose, 2010: Comprehensive automated quality assurance of daily surface observations. J. Appl. Meteor. Climatol., 49, 16151633.

    • Search Google Scholar
    • Export Citation
  • Field, C. B., and Coauthors, 2012: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Cambridge University Press, 582 pp.

  • Fisher, R. A., and L. H. C. Tippett, 1928: Limiting forms of the frequency distribution of the largest or smallest member of a sample. Math. Proc. Cambridge Philos. Soc., 24, 180190.

    • Search Google Scholar
    • Export Citation
  • Gnedenko, B. V., 1943: Sur la distribution limite du terme maximum d’une série aléatoire. Ann. Math., 44, 423453.

  • Groisman, P. Y., R. W. Knight, D. R. Easterling, T. R. Karl, G. C. Hegerl, and V. N. Razuvaev, 2005: Trends in intense precipitation in the climate record. J. Climate, 18, 13261350.

    • Search Google Scholar
    • Export Citation
  • Gumbel, E. J., 1958: Statistics of Extremes. Columbia University Press, 375 pp.

  • Hansen, J., R. Ruedy, T. Sato, and K. Lo, 2010: Global surface temperature change. Rev. Geophys., 48, RG4004, doi:10.1029/2010RG000345.

  • Hardwick-Jones, R., S. Westra, and A. Sharma, 2010: Observed relationships between extreme sub-daily precipitation, surface temperature and relative humidity. Geophys. Res. Lett., 37, L22805, doi:10.1029/2010GL045081.

    • Search Google Scholar
    • Export Citation
  • Hegerl, G. C., and Coauthors, 2007: Understanding and attributing climate change. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 663–745.

  • Hipel, K. W., and A. I. McLeod, 2005: Time Series Modeling of Water Resources and Environmental Systems. Developments in Water Science, Vol. 45, Elsevier, 1013 pp.

  • Jenkinson, A. F., 1955: The frequency distribution of the annual maximum (or minimum) values of meteorological elements. Quart. J. Roy. Meteor. Soc., 81, 158171.

    • Search Google Scholar
    • Export Citation
  • Kennedy, J. J., and Coauthors, 2010: How do we know the world has warmed? [in “State of the Climate in 2009”] Bull. Amer. Meteor. Soc., 91 (7), S26S27.

    • Search Google Scholar
    • Export Citation
  • Kharin, V. V., and F. Zwiers, 2000: Changes in the extremes of an ensemble of transient climate simulations with a coupled atmosphere–ocean GCM. J. Climate, 13, 37603788.

    • Search Google Scholar
    • Export Citation
  • Kharin, V. V., and F. Zwiers, 2005: Estimating extremes in transient climate change simulations. J. Climate, 18, 11561173.

  • Kharin, V. V., F. W. Zwiers, X. Zhang, and G. C. Hegerl, 2007: Changes in temperature and precipitation extremes in the IPCC ensemble global coupled model simulations. J. Climate, 20, 14191444.

    • Search Google Scholar
    • Export Citation
  • Kharin, V. V., F. W. Zwiers, X. Zhang, and M. Wehner, 2013: Changes in temperature and precipitation extremes in the CMIP5 ensemble. Climatic Change, doi:10.1007/s10584-013-0705-8, in press.

    • Search Google Scholar
    • Export Citation
  • Kiktev, D., D. Sexton, L. V. Alexander, and C. K. Folland, 2003: Comparison of modelled and observed trends in indicators of daily climate extremes. J. Climate, 16, 35603571.

    • Search Google Scholar
    • Export Citation
  • Kiktev, D., J. Caesar, L. V. Alexander, H. Shiogama, and M. Collier, 2007: Comparison of observed and multimodeled trends in annual extremes of temperature and precipitation. Geophys. Res. Lett., 34, L10702, doi:10.1029/2007GL029539.

    • Search Google Scholar
    • Export Citation
  • Leadbetter, M. R., G. Lindgren, and H. Rootzen, 1983: Extremes and Related Properties of Random Sequences and Processes. Springer-Verlag, 336 pp.

  • Lenderink, G., and E. van Meijgaard, 2008: Increase in hourly precipitation extremes beyond expectations from temperature changes. Nat. Geosci., 1, 511514.

    • Search Google Scholar
    • Export Citation
  • McLeod, A. I., 2011: Kendall: Kendall rank correlation and Mann–Kendall trend test, version 2.2. R package. [Available online at http://CRAN.R-project.org/package=Kendall.]

  • Mears, C., B. D. Santer, F. J. Wentz, K. E. Taylor, and M. Wehner, 2007: Relationship between temperature and precipitable water changes over tropical oceans. Geophys. Res. Lett., 34, L24709, doi:10.1029/2007GL031936.

    • Search Google Scholar
    • Export Citation
  • Menne, M. J., I. Durre, B. G. Gleason, T. G. Houston, and R. S. Vose, 2012: An overview of the Global Historical Climatology Network-Daily database. J. Atmos. Oceanic Technol., 29, 897910.

    • Search Google Scholar
    • Export Citation
  • Min, S. K., X. Zhang, F. W. Zwiers, P. Friederichs, and A. Hense, 2009: Signal detectability in extreme precipitation changes assessed from twentieth century climate simulations. Climate Dyn., 32, 95111.

    • Search Google Scholar
    • Export Citation
  • Min, S. K., X. Zhang, F. Zwiers, and G. C. Hegerl, 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378381.

    • Search Google Scholar
    • Export Citation
  • Mitchell, T. D., 2003: Pattern scaling: An examination of the accuracy of the technique for describing future climates. Climatic Change, 60, 217242.

    • Search Google Scholar
    • Export Citation
  • O’Gorman, P. A., and C. G. Muller, 2010: How closely do changes in surface and column water vapour follow Clausius–Clapeyron scaling in climate change simulations? Environ. Res. Lett., 5, 025207, doi:10.1088/1748-9326/5/2/025207.

    • Search Google Scholar
    • Export Citation
  • Padoan, S. A., M. Ribatet, and S. A. Sisson, 2010: Likelihood-based inference for max-stable processes. J. Amer. Stat. Assoc., 105, 263277.

    • Search Google Scholar
    • Export Citation
  • Sanchez-Lugo, A., J. J. Kennedy, and P. Berrisford, 2012: Surface temperature [in “State of the Climate in 2011”]. Bull. Amer. Meteor. Soc., 93 (7), S14S15.

    • Search Google Scholar
    • Export Citation
  • Semenov, V. A., and L. Bengtsson, 2002: Secular trends in daily precipitation characteristics: Greenhouse gas simulation with a coupled AOGCM. Climate Dyn., 19, 123140.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., and Coauthors, 2012: Changes in climate extremes and their impacts on the natural physical environment. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, C. B. Field et al., Eds., Cambridge University Press, 109–230.

  • Sherwood, S. C., W. Ingram, Y. Tsushima, M. Satoh, M. Roberts, P. L. Vidale, and P. A. O’Gorman, 2010a: Relative humidity changes in a warmer climate. J. Geophys. Res., 115, D09104, doi:10.1029/2009JD012585.

    • Search Google Scholar
    • Export Citation
  • Sherwood, S. C., R. Roca, T. M. Weckwerth, and N. G. Andronova, 2010b: Tropospheric water vapor, convection, and climate. Rev. Geophys., 48, RG2001, doi:10.1029/2009RG000301.

    • Search Google Scholar
    • Export Citation
  • Simmons, A., K. M. Willett, P. D. Jones, P. W. Thorne, and D. Dee, 2010: Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational datasets. J. Geophys. Res., 115, D01110, doi:10.1029/2009JD012442.

    • Search Google Scholar
    • Export Citation
  • Stephenson, A. G., 2002: EVD: Extreme value distributions. R News, No. 2(2), R Foundation, Vienna, Austria, 31–32. [Available online at http://CRAN.R-project.org/doc/Rnews/.]

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., 2011: Changes in precipitation with climate change. Climate Res., 47, 123138.

  • Trenberth, K. E., 2012: Framing the way to relate climate extremes to climate change. Climatic Change, 115, 283290.

  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 12051217.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., and Coauthors, 2007: Observations: Surface and atmospheric climate change. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 235–336.

  • Utsumi, N., S. Seto, S. Kanae, E. E. Maeda, and T. Oki, 2011: Does higher surface temperature intensify extreme precipitation? Geophys. Res. Lett., 38, L16708, doi:10.1029/2011GL048426.

    • Search Google Scholar
    • Export Citation
  • von Mises, R., 1954: La distribution de la plus grande de n valeurs. Probability and Statistics, Vol. 2, Selected Papers of Richard von Mises, Ph. Frank et al., Eds., American Mathematical Society, 271–294.

  • von Storch, H., and F. W. Zwiers, 1999: Statistical Analysis in Climate Research. Cambridge University Press, 484 pp.

  • Voss, R., W. May, and E. Roeckner, 2002: Enhanced resolution modelling study on anthropogenic climate change: Changes in extremes of the hydrological cycle. Int. J. Climatol., 22, 755777.

    • Search Google Scholar
    • Export Citation
  • Westra, S., and S. A. Sisson, 2011: Detection of non-stationarity in precipitation extremes using a max-stable process model. J. Hydrol., 406, 119128.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 1997: Resampling hypothesis tests for autocorrelated fields. J. Climate, 10, 6582.

  • Wilks, D. S., 2011: Statistical Methods in the Atmospheric Sciences. Elsevier, 676 pp.

  • Willett, K. M., N. P. Gillet, P. D. Jones, and P. W. Thorne, 2007: Attribution of observed surface humidity changes to human influence. Nature, 449, 710713.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., L. V. Alexander, G. C. Hegerl, P. Jones, A. M. G. Klein Tank, T. C. Peterson, B. Trewin, and F. W. Zwiers, 2011: Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdiscip. Rev.: Climate Change, 2, 851870.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 11145 2596 242
PDF Downloads 7345 1892 201