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Climatic Change

, Volume 156, Issue 1–2, pp 105–120 | Cite as

The local dependency of precipitation on historical changes in temperature

  • Conrad WaskoEmail author
  • Rory Nathan
Article

Abstract

Globally, mean and extreme precipitation will increase with climate change. This is largely controlled by moisture and energy availability which is linked to temperature. Therefore, changes in precipitation are regularly presented proportional to a change in mean global temperature, and temperature is often proposed as a covariate for projecting precipitation with climatic change. However, studies which investigate the association between precipitation and temperature largely focus on the day-to-day association between precipitation and temperature fluctuations at a gauged location, which is not necessarily equivalent to changes in precipitation at climatic spatial and time scales. To assess whether temperature changes may help inform changes in precipitation with climatic change, we evaluate the historical relationship between precipitation and annual temperature fluctuations. We find positive correlations between precipitation and mean annual dew point temperature. These associations are strongest for annual average precipitation and weakest for the shortest, most extreme precipitation. We find that the strength of this correlation is more strongly linked to the number of rain days, rather than the precipitation depth itself. When dry-bulb temperatures are used in place of dew point temperature, the association between precipitation and temperature is either negative or zero. As a strong association between wet day dry-bulb and dew point temperatures exists, changes in temperature may aid in understanding the changes to precipitation as global temperatures increase. However, as the precipitation-dew point correlation is not necessarily physically related to the precipitation depth but rather to precipitation occurrence; precipitation-temperature sensitivities need to be interpreted with caution.

Keywords

Precipitation Precipitation extremes Temperature Dew point Trends Climate change 

Notes

Funding information

Conrad Wasko is funded by the University of Melbourne McKenzie Postdoctoral Fellowships Program and acknowledges assistance from Ewen Su.

Supplementary material

10584_2019_2523_MOESM1_ESM.docx (272 kb)
ESM 1 (DOCX 271 kb)

References

  1. Agilan V, Umamahesh NV (2017) What are the best covariates for developing non-stationary rainfall Intensity-Duration-Frequency relationship? Adv. Water Resour. 101:11–22.  https://doi.org/10.1016/j.advwatres.2016.12.016 CrossRefGoogle Scholar
  2. Alexander LV, Arblaster JM (2017) Historical and projected trends in temperature and precipitation extremes in Australia in observations and CMIP5. Weather Clim Extrem 15:34–56.  https://doi.org/10.1016/j.wace.2017.02.001 CrossRefGoogle Scholar
  3. Ali H, Mishra V (2017) Contrasting response of rainfall extremes to increase in surface air and dewpoint temperatures at urban locations in India. Sci Rep 7:1228.  https://doi.org/10.1038/s41598-017-01306-1 CrossRefGoogle Scholar
  4. Ali H, Fowler HJ, Mishra V (2018) Global observational evidence of strong linkage between dew point temperature and precipitation extremes. Geophys Res Lett 45:320–330.  https://doi.org/10.1029/2018GL080557 CrossRefGoogle Scholar
  5. Allan RP, Soden BJ (2008) Atmospheric warming and the amplification of precipitation extremes. Science (80- ) 321:1481–1484.  https://doi.org/10.1126/science.1160787 CrossRefGoogle Scholar
  6. Allan RP, Soden BJ, John VO et al (2010) Current changes in tropical precipitation. Environ Res Lett 5:025205.  https://doi.org/10.1088/1748-9326/5/2/025205 CrossRefGoogle Scholar
  7. Allan RP, Liu C, Zahn M et al (2014) Physically consistent responses of the global atmospheric hydrological cycle in models and observations. Surv Geophys 35:533–552.  https://doi.org/10.1007/s10712-012-9213-z CrossRefGoogle Scholar
  8. Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrologic cycle. Nature 419:224–232.  https://doi.org/10.1038/nature01092 CrossRefGoogle Scholar
  9. Ban N, Schmidli J, Schär C (2014) Evaluation of the new convective-resolving regional climate modeling approach in decade-long simulations. J Geophys Res Atmos 119:7889–7907.  https://doi.org/10.1002/2014JD021478.Received CrossRefGoogle Scholar
  10. Bao J, Sherwood SC, Alexander LV, Evans JP (2017) Future increases in extreme precipitation exceed observed scaling rates. Nat Clim Chang 7:128–132.  https://doi.org/10.1038/nclimate3201 CrossRefGoogle Scholar
  11. Barbero R, Fowler HJ, Lenderink G, Blenkinsop S (2017a) Is the intensification of precipitation extremes with global warming better detected at hourly than daily resolutions? Geophys Res Lett 44:974–983.  https://doi.org/10.1002/2016GL071917 CrossRefGoogle Scholar
  12. Barbero R, Westra S, Lenderink G, Fowler HJ (2017b) Temperature-extreme precipitation scaling: a two-way causality? Int J Climatol 38:e1274–e1279.  https://doi.org/10.1002/joc.5370 CrossRefGoogle Scholar
  13. Blenkinsop S, Chan SC, Kendon EJ et al (2015) Temperature influences on intense UK hourly precipitation and dependency on large-scale circulation. Environ Res Lett 10:054021.  https://doi.org/10.1088/1748-9326/10/5/054021 CrossRefGoogle Scholar
  14. Boucher O, Randall D, Artaxo P et al (2013) Clouds and aerosols. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 571–657Google Scholar
  15. Bui A, Johnson F, Wasko C (2019) The relationship of atmospheric air temperature and dew point temperature to extreme rainfall. Environ Res Lett.  https://doi.org/10.1088/1748-9326/ab2a26 CrossRefGoogle Scholar
  16. Busuioc A, Birsan MV, Carbunaru D et al (2016) Changes in the large-scale thermodynamic instability and connection with rain shower frequency over Romania: verification of the Clausius-Clapeyron scaling. Int J Climatol 2034:2015–2034.  https://doi.org/10.1002/joc.4477 CrossRefGoogle Scholar
  17. Chan SC, Kendon EJ, Roberts NM et al (2016) Downturn in scaling of UK extreme rainfall with temperature for future hottest days. Nat Geosci 9:24–28.  https://doi.org/10.1038/ngeo2596 CrossRefGoogle Scholar
  18. Collins M, Knutti R, Arblaster J et al (2013) Long-term climate change: projections, commitments and irreversibility. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 1029–1136Google Scholar
  19. CSIRO & BOM (2016) State of the ClimateGoogle Scholar
  20. Da Silva N, Mailler S, Drobinski P (2019) Aerosol indirect effects on the temperature-precipitation scaling. Atmos Chem Phys Discuss in review 1–25.  https://doi.org/10.5194/acp-2018-1334
  21. Dai A, Fung IY, Del Genio AD (1997) Surface observed global land precipitation variations during 1900–88. J Clim 10:2943–2962.  https://doi.org/10.1175/1520-0442(1997)010<2943:SOGLPV>2.0.CO;2 CrossRefGoogle Scholar
  22. Drobinski P, Da Silva N, Panthou G et al (2018) Scaling precipitation extremes with temperature in the Mediterranean: past climate assessment and projection in anthropogenic scenarios. Clim Dyn 51:1237–1257.  https://doi.org/10.1007/s00382-016-3083-x CrossRefGoogle Scholar
  23. Fujibe F (2013) Clausius-Clapeyron-like relationship in multidecadal changes of extreme short-term precipitation and temperature in Japan. Atmos Sci Lett 14:127–132.  https://doi.org/10.1002/asl2.428 CrossRefGoogle Scholar
  24. Groisman PY, Knight RW, Easterling DR et al (2005) Trends in intense precipitation in the climate record. J Clim 18:1326–1350.  https://doi.org/10.1175/JCLI3339.1 CrossRefGoogle Scholar
  25. Guerreiro SB, Fowler HJ, Barbero R et al (2018) Detection of continental-scale intensification of hourly rainfall extremes. Nat Clim Chang 8:803–807.  https://doi.org/10.1038/s41558-018-0245-3 CrossRefGoogle Scholar
  26. Hardwick Jones R, Westra S, Sharma A (2010) Observed relationships between extreme sub-daily precipitation, surface temperature, and relative humidity. Geophys Res Lett 37:L22805.  https://doi.org/10.1029/2010GL045081 CrossRefGoogle Scholar
  27. Hartmann DL, Klein Tank AMG, Rusticucci M et al (2013) Observations: atmosphere and surface. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp 159–254Google Scholar
  28. Head L, Adams M, Mcgregor H, Toole S (2014) Climate change and Australia. Wiley Interdiscip Rev WIREs Clim Chang 5:175–197CrossRefGoogle Scholar
  29. Hettiarachchi S, Wasko C, Sharma A (2018) Increase in flood risk resulting from climate change in a developed urban watershed – the role of storm temporal patterns. Hydrol Earth Syst Sci 22:2041–2056.  https://doi.org/10.5194/hess-22-2041-2018 CrossRefGoogle Scholar
  30. Hughes L (2003) Climate change and Australia: trends, projections and impacts. Austral Ecol 28:423–443.  https://doi.org/10.1046/j.1442-9993.2003.01300.x CrossRefGoogle Scholar
  31. Jakob D, Walland D (2016) Variability and long-term change in Australian temperature and precipitation extremes. Weather Clim. Extrem. 14:36–55.  https://doi.org/10.1016/j.wace.2016.11.001 CrossRefGoogle Scholar
  32. Johnson F, Sharma A (2009) Measurement of GCM skill in predicting variables relevant for hydroclimatological assessments. J Clim 22:4373–4382.  https://doi.org/10.1175/2009JCLI2681.1 CrossRefGoogle Scholar
  33. Kendon EJ, Roberts NM, Fowler HJ et al (2014) Heavier summer downpours with climate change revealed by weather forecast resolution model. Nat Clim Chang 4:570–576.  https://doi.org/10.1038/nclimate2258 CrossRefGoogle Scholar
  34. Kharin VV, Zwiers FW, Zhang X, Wehner M (2013) Changes in temperature and precipitation extremes in the CMIP5 ensemble. Clim Chang 119:345–357.  https://doi.org/10.1007/s10584-013-0705-8 CrossRefGoogle Scholar
  35. Kirtman B, Power S, Adedoyin J et al (2013) Near-term climate change: projections and predictability. In: Stocker T, Plattner G-K, Tignor M et al (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 953–1028Google Scholar
  36. Lenderink G, Attema J (2015) A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands. Environ Res Lett 10:085001.  https://doi.org/10.1088/1748-9326/10/8/085001 CrossRefGoogle Scholar
  37. Lenderink G, van Meijgaard E (2008) Increase in hourly precipitation extremes beyond expectations from temperature changes. Nat Geosci 1:511–514.  https://doi.org/10.1038/ngeo262 CrossRefGoogle Scholar
  38. Lenderink G, van Meijgaard E (2010) Linking increases in hourly precipitation extremes to atmospheric temperature and moisture changes. Environ Res Lett 5:025208.  https://doi.org/10.1088/1748-9326/5/2/025208 CrossRefGoogle Scholar
  39. Lenderink G, Mok HY, Lee TC, van Oldenborgh GJ (2011) Scaling and trends of hourly precipitation extremes in two different climate zones – Hong Kong and the Netherlands. Hydrol Earth Syst Sci 15:3033–3041.  https://doi.org/10.5194/hess-15-3033-2011 CrossRefGoogle Scholar
  40. Lenderink G, Barbero R, Loriaux JM, Fowler HJ (2017) Super-Clausius-Clapeyron scaling of extreme hourly convective precipitation and its relation to large-scale atmospheric conditions. J Clim 30:6037–6052.  https://doi.org/10.1175/JCLI-D-16-0808.1 CrossRefGoogle Scholar
  41. Li J, Wasko C, Johnson F et al (2018) Can regional climate modeling capture the observed changes in spatial organization of extreme storms at higher temperatures? Geophys Res Lett 45:4475–4484.  https://doi.org/10.1029/2018GL077716 CrossRefGoogle Scholar
  42. Loriaux JM, Lenderink G, De Roode SR, Siebesma AP (2013) Understanding convective extreme precipitation scaling using observations and an entraining plume model. J Atmos Sci 70:3641–3655.  https://doi.org/10.1175/JAS-D-12-0317.1 CrossRefGoogle Scholar
  43. Lucas C (2010) A high-quality historical humidity database for Australia. Melbourne, AustraliaGoogle Scholar
  44. Manola I, van den Hurk B, De Moel H, Aerts JCJH (2018) Future extreme precipitation intensities based on a historic event. Hydrol Earth Syst Sci 22:3777–3788.  https://doi.org/10.5194/hess-22-3777-2018 CrossRefGoogle Scholar
  45. Molnar P, Fatichi S, Gaál L et al (2015) Storm type effects on super Clausius–Clapeyron scaling of intense rainstorm properties with air temperature. Hydrol Earth Syst Sci 19:1753–1766.  https://doi.org/10.5194/hess-19-1753-2015 CrossRefGoogle Scholar
  46. Muller CJ, O’Gorman PA, Back LE (2011) Intensification of precipitation extremes with warming in a cloud-resolving model. J Clim 24:2784–2800.  https://doi.org/10.1175/2011JCLI3876.1 CrossRefGoogle Scholar
  47. Nicholls N, Della-Marta P, Collins D (2004) 20th century changes in temperature and rainfall in New South Wales. Aust Meteorol Mag 53:263–268Google Scholar
  48. O’Gorman PA (2015) Precipitation extremes under climate change. Curr Clim Chang Rep 1:49–59.  https://doi.org/10.1007/s40641-015-0009-3 CrossRefGoogle Scholar
  49. O’Gorman PA, Schneider T (2009) The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc Natl Acad Sci U S A 106:14773–14777.  https://doi.org/10.1073/pnas.0907610106 CrossRefGoogle Scholar
  50. Panthou G, Mailhot A, Laurence E, Talbot G (2014) Relationship between surface temperature and extreme rainfalls: a multi-time-scale and event-based analysis. J Hydrometeorol 15:1999–2011.  https://doi.org/10.1175/JHM-D-14-0020.1 CrossRefGoogle Scholar
  51. Park I-H, Min S-K (2017) Role of convective precipitation in the relationship between subdaily extreme precipitation and temperature. J Clim 30:9527–9537.  https://doi.org/10.1175/JCLI-D-17-0075.1 CrossRefGoogle Scholar
  52. Peel M, Finlayson B, McMahon T (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci 11:1633–1644CrossRefGoogle Scholar
  53. Pfahl S, O’Gorman PA, Fischer EM (2017) Understanding the regional pattern of projected future changes in extreme precipitation. Nat Clim Chang 7:423–427.  https://doi.org/10.1038/nclimate3287 CrossRefGoogle Scholar
  54. Roderick TP, Wasko C, Sharma A (2019) Atmospheric moisture measurements explain increases in tropical rainfall extremes. Geophys Res Lett 46:1375–1382.  https://doi.org/10.1029/2018GL080833 CrossRefGoogle Scholar
  55. Schleiss M (2018) How intermittency affects the rate at which rainfall extremes respond to changes in temperature. Earth Syst Dynam 9:955–968.  https://doi.org/10.5194/esd-9-955-2018 CrossRefGoogle Scholar
  56. Seidel DJ, Fu Q, Randel WJ, Reichler TJ (2008) Widening of the tropical belt in a changing climate. Nat Geosci 1:21–24.  https://doi.org/10.1038/ngeo.2007.38 CrossRefGoogle Scholar
  57. Singh MS, O’Gorman PA (2014) Influence of microphysics on the scaling of precipitation extremes with temperature. Geophys Res Lett 41:6037–6044.  https://doi.org/10.1002/2014GL061222 CrossRefGoogle Scholar
  58. Singleton A, Toumi R (2013) Super-Clausius-Clapeyron scaling of rainfall in a model squall line. Q J R Meteorol Soc 139:334–339.  https://doi.org/10.1002/qj.1919 CrossRefGoogle Scholar
  59. Trenberth KE (2011) Changes in precipitation with climate change. Clim Res 47:123–138.  https://doi.org/10.3354/cr00953 CrossRefGoogle Scholar
  60. Trenberth KE, Shea DJ (2005) Relationships between precipitation and surface temperature. Geophys Res Lett 32:L14703.  https://doi.org/10.1029/2005GL022760 CrossRefGoogle Scholar
  61. Trenberth KE, Dai A, Rasmussen RM, Parsons DB (2003) The changing character of precipitation. Bull Am Meteorol Soc 84:1205–1217.  https://doi.org/10.1175/BAMS-84-9-1205 CrossRefGoogle Scholar
  62. Trenberth KE, Jones PD, Ambenje P et al (2007) Observations: surface and atmospheric climate change. In: Solomon S, Qin D, Manning M et al (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USAGoogle Scholar
  63. Utsumi N, Seto S, Kanae S et al (2011) Does higher surface temperature intensify extreme precipitation? Geophys Res Lett 38:L16708.  https://doi.org/10.1029/2011GL048426 CrossRefGoogle Scholar
  64. Vautard R, Yiou P, D’Andrea F et al (2007) Summertime European heat and drought waves induced by wintertime Mediterranean rainfall deficit. Geophys Res Lett 34:1–5.  https://doi.org/10.1029/2006GL028001 CrossRefGoogle Scholar
  65. Wallace J, Hobbs P (2006) Atmospheric science: an introductory survey, 2nd edn. Academic PressGoogle Scholar
  66. Wasko C, Sharma A (2014) Quantile regression for investigating scaling of extreme precipitation with temperature. Water Resour Res 50:3608–3614.  https://doi.org/10.1002/2013WR015194 CrossRefGoogle Scholar
  67. Wasko C, Sharma A (2017) Continuous rainfall generation for a warmer climate using observed temperature sensitivities. J Hydrol 544:575–590.  https://doi.org/10.1016/j.jhydrol.2016.12.002 CrossRefGoogle Scholar
  68. Wasko C, Sharma A, Johnson F (2015) Does storm duration modulate the extreme precipitation-temperature scaling relationship? Geophys Res Lett 42:8783–8790.  https://doi.org/10.1002/2015GL066274 CrossRefGoogle Scholar
  69. Wasko C, Parinussa RM, Sharma A (2016) A quasi-global assessment of changes in remotely sensed rainfall extremes with temperature. Geophys Res Lett 43:12,659–12,668.  https://doi.org/10.1002/2016GL071354 CrossRefGoogle Scholar
  70. Wasko C, Lu WT, Mehrotra R (2018) Relationship of extreme precipitation, dry-bulb temperature, and dew point temperature across Australia. Environ Res Lett 13:074031.  https://doi.org/10.1088/1748-9326/aad135 CrossRefGoogle Scholar
  71. Westra S, Sisson SA (2011) Detection of non-stationarity in precipitation extremes using a max-stable process model. J Hydrol 406:119–128.  https://doi.org/10.1016/j.jhydrol.2011.06.014 CrossRefGoogle Scholar
  72. Westra S, Alexander L, Zwiers F (2013a) Global increasing trends in annual maximum daily precipitation. J Clim 26:3904–3918.  https://doi.org/10.1175/JCLI-D-12-00502.1 CrossRefGoogle Scholar
  73. Westra S, Evans JP, Mehrotra R, Sharma A (2013b) A conditional disaggregation algorithm for generating fine time-scale rainfall data in a warmer climate. J Hydrol 479:86–99.  https://doi.org/10.1016/j.jhydrol.2012.11.033 CrossRefGoogle Scholar
  74. Westra S, Fowler HJ, Evans JP et al (2014) Future changes to the intensity and frequency of short-duration extreme rainfall. Rev Geophys 52:522–555.  https://doi.org/10.1002/2014RG000464 CrossRefGoogle Scholar
  75. Zhang X, Zwiers FW, Hegerl GC et al (2007) Detection of human influence on twentieth-century precipitation trends. Nature 448:461–465.  https://doi.org/10.1038/nature06025 CrossRefGoogle Scholar
  76. Zhang X, Zwiers FW, Li G et al (2017) Complexity in estimating past and future extreme short-duration rainfall. Nat Geosci 10:255–259.  https://doi.org/10.1038/ngeo2911 CrossRefGoogle Scholar
  77. Zhang W, Villarini G, Wehner M (2019) Contrasting the responses of extreme precipitation to changes in surface air and dew point temperatures. Clim Chang.  https://doi.org/10.1007/s10584-019-02415-8 CrossRefGoogle Scholar
  78. Zheng F, Westra S, Leonard M (2015) Opposing local precipitation extremes. Nat Clim Chang 5:389–390.  https://doi.org/10.1038/nclimate2579 CrossRefGoogle Scholar

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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Infrastructure EngineeringThe University of MelbourneParkvilleAustralia

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