Steeper temporal distribution of rain intensity at higher temperatures within Australian storms

Journal name:
Nature Geoscience
Year published:
Published online

The mechanisms that cause changes in precipitation, as well as the resulting storm dynamics, under potential future warming remain debated1, 2, 3. Measured sensitivities of precipitation to temperature variations in the present climate have been used to constrain model predictions4, 5, debate precipitation mechanisms2, 3 and speculate on future changes to precipitation6 and flooding7. Here, we analyse data sets of precipitation measurements at 6-min resolution from 79 locations throughout Australia, covering a broad range of climate zones, along with sub-daily temperature measurements of varying resolution. We investigate the relationship between temporal patterns of precipitation intensity within storm bursts and temperature variations in the present climate by calculating the scaling of the precipitation fractions within each storm burst. We find that in the present climate, a less uniform temporal pattern of precipitation—more intense peak precipitation and weaker precipitation during less intense times—is found at higher temperatures, regardless of the climatic region and season. We suggest invigorating storm dynamics could be associated with the warming temperatures expected over the course of the twenty-first century, which could lead to increases in the magnitude and frequency of short-duration floods.

At a glance


  1. Scaling of hourly storm burst temporal pattern.
    Figure 1: Scaling of hourly storm burst temporal pattern.

    a, Schematic of temporal pattern scaling. The storm burst is divided into five equal periods and the precipitation fractions are ranked from largest to smallest. The two largest fractions scale positively, whereas the smallest three fractions scale negatively, resulting in a less uniform temporal pattern. b, Measured scaling for the largest precipitation fraction (α1). c, Measured scaling for the smallest precipitation fraction (α5). Crosses indicate statistical significance at the 95% confidence level testing against the null hypothesis that the slope of the regression line is zero. The circle area is proportional to scaling.

  2. Scaling of volume, first precipitation fraction, and last precipitation fraction, plotted against station latitude.
    Figure 2: Scaling of volume, first precipitation fraction, and last precipitation fraction, plotted against station latitude.

    a, Results for a 60-min storm burst duration. b, Result for varying storm burst duration. The thick lines are smoothing splines fitted to the measured scaling at the stations of interest. The lines in order of decreasing thickness and increasing transparency are for storm bursts of 60, 120, 180, 360 and 720 min, each with five equal periods. Scaling of volume (αV) is in black, first precipitation fraction (α1) in red, and last precipitation fraction (α5) in blue.


  1. Haerter, J. O. & Berg, P. Unexpected rise in extreme precipitation caused by a shift in rain type? Nature Geosci. 2, 372373 (2009).
  2. Berg, P., Moseley, C. & Haerter, J. O. Strong increase in convective precipitation in response to higher temperatures. Nature Geosci. 6, 181185 (2013).
  3. Collins, M. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. et al.) 10291136 (IPCC, Cambridge Univ. Press, 2013).
  4. Boucher, O. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. et al.) 571657 (IPCC, Cambridge Univ. Press, 2013).
  5. Lenderink, G. & van Meijgaard, E. Increase in hourly precipitation extremes beyond expectations from temperature changes. Nature Geosci. 1, 511514 (2008).
  6. Kirtman, B. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. et al.) 9531028 (IPCC, Cambridge Univ. Press, 2013).
  7. Westra, S. et al. Future changes to the intensity and frequency of short-duration extreme rainfall. Rev. Geophys. 52, 522555 (2014).
  8. Alexander, L. V. et al. Global observed changes in daily climate extremes of temperature and precipitation. J. Geophys. Res. 111, D05109 (2006).
  9. Westra, S., Alexander, L. & Zwiers, F. Global increasing trends in annual maximum daily precipitation. J. Clim. 26, 39043918 (2013).
  10. Hartmann, D. L. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. et al.) 159254 (IPCC, Cambridge Univ. Press, 2013).
  11. Trenberth, K. E., Dai, A., Rasmussen, R. M. & Parsons, D. B. The changing character of precipitation. Bull. Am. Meteorol. Soc. 84, 12051217 (2003).
  12. Hardwick-Jones, R., Westra, S. & Sharma, A. Observed relationships between extreme sub-daily precipitation, surface temperature, and relative humidity. Geophys. Res. Lett. 37, L22805 (2010).
  13. Utsumi, N., Seto, S., Kanae, S., Maeda, E. E. & Oki, T. Does higher surface temperature intensify extreme precipitation? Geophys. Res. Lett. 38, L16708 (2011).
  14. Wasko, C. & Sharma, A. Quantile regression for investigating scaling of extreme precipitation with temperature. Wat. Resour. Res. 50, 36083614 (2014).
  15. Moseley, C., Berg, P. & Haerter, J. O. Probing the precipitation life cycle by iterative rain cell tracking. J. Geophys. Res. 118, 1336113370 (2013).
  16. Singleton, A. & Toumi, R. Super-Clausius–Clapeyron scaling of rainfall in a model squall line. Q. J. R. Meteorol. Soc. 139, 334339 (2013).
  17. Loriaux, J. M., Lenderink, G., De Roode, S. R. & Siebesma, a. P. Understanding convective extreme precipitation scaling using observations and an entraining plume model. J. Atmos. Sci. 70, 36413655 (2013).
  18. Panthou, G., Mailhot, A., Laurence, E. & Talbot, G. Relationship between surface temperature and extreme rainfalls: A multi-timescale and event-based analysis. J. Hydrometeorol. 15, 19992011 (2014).
  19. Westra, S. & Sisson, S. A. Detection of non-stationarity in precipitation extremes using a max-stable process model. J. Hydrol. 406, 119128 (2011).
  20. Kennedy, M., Turner, L., Canterford, R. & Pearce, H. Temporal Distributions within Rainfall Bursts (Hydrology Report Series 1, Bureau of Meteorology, 1991)
  21. Pilgrim, D. et al. in Australian Rainfall and Runoff—A Guide to Flood Estimation Book 2, Section 2 (The Institution of Engineers, 1997)
  22. Lenderink, G. & van Meijgaard, E. Linking increases in hourly precipitation extremes to atmospheric temperature and moisture changes. Environ. Res. Lett. 5, 025208 (2010).
  23. Tremblay, A. The stratiform and convective components of surface precipitation. J. Atmos. Sci. 62, 15131528 (2005).
  24. Ruiz-Leo, A.M., Hernández, E., Queralt, S. & Maqueda, G. Convective and stratiform precipitation trends in the Spanish Mediterranean coast. Atmos. Res. 119, 4655 (2013).
  25. Berg, P. et al. Seasonal characteristics of the relationship between daily precipitation intensity and surface temperature. J. Geophys. Res. 114, D18102 (2009).
  26. Kirchner, J. W. Catchments as simple dynamical systems: Catchment characterization, rainfall-runoff modeling, and doing hydrology backward. Wat. Resour. Res. 45, W02429 (2009).
  27. Pan, M. & Wood, E. F. Inverse streamflow routing. Hydrol. Earth Syst. Sci. 17, 45774588 (2013).
  28. Chow, V., Maidment, D. & Mays, L. Applied Hydrology (McGraw-Hill, 1988).
  29. Brutsaert, W. Hydrology—An Introduction (Cambridge Univ. Press, 2005).
  30. Pilgrim, D. in Australian Rainfall and Runoff—A Guide to Flood Estimation Book 4, Section 1 (The Institution of Engineers, 1997)

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C.W. and A.S. conceived the initial idea. C.W. performed the analysis. C.W. and A.S. contributed to the manuscript.

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