Climate Dynamics

, Volume 48, Issue 5–6, pp 1723–1747 | Cite as

Regional climate projections of mean and extreme climate for the southwest of Western Australia (1970–1999 compared to 2030–2059)

Article

Abstract

Projections of future climate change (1970–1999 compared to 2030–2059) for southwest Western Australia (SWWA) are analysed for a regional climate model (RCM) ensemble using the Weather Research and Forecasting Model with boundary conditions from three CMIP3 general circulation models (GCMs); CCSM3, CSIROmk3.5 and ECHAM5. We show that the RCM adds value to the GCM and we suggest that this is through improved representation of regional scale topography and enhanced land–atmosphere interactions. Our results show that the mean daytime temperature increase is larger than the nighttime increase, attributed to reduced soil moisture and hence increased surface sensible heat flux in the model, and there is statistically significant evidence that the variance of minimum temperatures will increase. Changes in summer rainfall are uncertain, with some models showing rainfall increases and others projecting reductions. All models show very large fluctuations in summer rainfall intensity which has important implications because of the increased risk of flash flooding and erosion of arable land. There is model consensus indicating a decline in winter rainfall and the spatial distribution of this rainfall decline is influenced by regional scale topography in two of the three simulations. Winter rainfall reduction is consistent with the historical trend of declining rainfall in SWWA, which has been attributed in previous research to a reduction in the number of fronts passing over the region. The continuation of this trend is evident in all models by an increase in winter mean sea level pressure in SWWA, and a reduced number of winter front days. Winter rainfall does not show any marked variations in daily intensity.

Keywords

Regional climate modelling WRF Western Australia 

Notes

Acknowledgments

This research was supported by an Australian Grains Research and Development Corporation (GRDC) Grant (MCV0013). Julia Andrys is supported by an Australian Postgraduate Award and a GRDC Top Up Scholarship. Jatin Kala was supported by the Australian Research Council Centre of Excellence for Climate Systems Science (CE110001028) for part of this work. The research group lead by Associate Professor Jason Evans at the University of New South Wales, Australia, provided the modified version of WRFv3.3 used in this study, and assisted in the pre-processing of the input data. Dr. Ruth Lorenz from the University of New South Wales provided the scripts to account for serial correlation in t tests. Computational modeling was supported by the Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia. It was funded under the National Computational Merit Allocation Scheme and the Pawsey Partner Allocation Scheme. All of this support is gratefully acknowledged.

References

  1. Alexander LV, Arblaster JM (2009) Assessing trends in observed and modelled climate extremes over Australia in relation to future projections. Int J Climatol 29:417–435. doi: 10.1002/joc.1730 CrossRefGoogle Scholar
  2. Andrys J, Lyons TJ, Kala J (2015a) Evaluation of a WRF ensemble using GCM boundary conditions to quantify mean and extreme climate for the southwest of Western Australia (1970–1999). Int J Climatol. doi: 10.1002/joc.4641 Google Scholar
  3. Andrys J, Lyons TJ, Kala J (2015b) Multi-decadal evaluation of WRF downscaling capabilities over Western Australia in simulating rainfall and temperature extremes. J Appl Meteorol Climatol 54:370–394. doi: 10.1175/JAMC-D-14-0212.1 CrossRefGoogle Scholar
  4. Argueso D, Hidalgo-Mutildenoz JM, Gacuteamiz-Fortis SR, Esteban-Parra MJ, Dudhia J, Castro-Diez Y (2011) Evaluation of WRF parameterizations for climate sutdies over Southern Spain using a multi-step regionalization. J Clim 24:5633–5651. doi: 10.1175/JCLI-D-11-00073.1 CrossRefGoogle Scholar
  5. Argüeso D, Hidalgo-Muñoz JM, Gámiz-Fortis SR, Esteban-Parra MJ, Castro-Díez Y (2012) Evaluation of WRF mean and extreme precipitation over Spain: present climate (1970–99). J Clim 25:4883–4897. doi: 10.1175/JCLI-D-11-00276.1 CrossRefGoogle Scholar
  6. Asseng S, Foster I, Turner NC (2011) The impact of temperature variability on wheat yields. Glob Change Biol 17:997–1012. doi: 10.1111/j.1365-2486.2010.02262.x CrossRefGoogle Scholar
  7. Bates BC, Hope P, Ryan B, Smith I, Charles S (2008) Key findings from the Indian ocean climate initiative and their impact on policy development in Australia. Clim Change 89:339–354. doi: 10.1007/s10584-007-9390-9 CrossRefGoogle Scholar
  8. Bengtsson L, Hodges KI, Keenlyside N (2009) Will extratropical storms intensify in a warmer climate? J Clim 22:2276–2301. doi: 10.1175/2008JCLI2678.1 CrossRefGoogle Scholar
  9. Cai W, Cowan T, Sullivan A, Ribbe J, Shi G (2011) Are anthropogenic aerosols responsible for the northwest Australia summer rainfall increase? A CMIP3 perspective and implications. J Clim 24:2556–2564. doi: 10.1175/2010JCLI3832.1 CrossRefGoogle Scholar
  10. Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129:569–585CrossRefGoogle Scholar
  11. Collins M, Knutti R, Arblaster JM, Dufresne JL, Fichefet T, Friedlingstein P, Gao X, Gutowski WJ, Johns T, Krinner G (2013) Long-term climate change: projections, commitments and irreversibility. In: 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, Cambridge University Press, p 1054Google Scholar
  12. Collins WD, Rasch PJ, Boville BA, Hack JJ, McCaa JR, Williamson DL, Briegleb BP, Bitz CM, Lin SJ, Zhang M (2006) The formulation and atmospheric simulation of the Community Atmosphere Model version 3 (CAM3). J Clim 19:2144–2161. doi: 10.1175/JCLI3760.1 CrossRefGoogle Scholar
  13. Cover TM, Thomas JA (2012) Elements of information theory, 2nd edn. Wiley, HobokenGoogle Scholar
  14. Dai A, Trenberth KE, Karl TR (1999) Effects of clouds, soil moisture, precipitation, and water vapor on diurnal temperature range. J Clim 12:2451–2473. doi: 10.1175/1520-0442(1999)012<2451:EOCSMP>2.0.CO;2 CrossRefGoogle Scholar
  15. Dee DP, Uppala SM, Simmons aJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda Ma, Balsamo G, Bauer P, Bechtold P, Beljaars aCM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer aJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally aP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thépaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  16. Dittus AJ, Karoly DJ, Lewis SC, Alexander LV (2014) An investigation of some unexpected frost day increases in southern Australia. Aust Meteorol Oceanogr J 64:261–271Google Scholar
  17. Donat MG, Alexander LV (2012) The shifting probability distribution of global daytime and night-time temperatures. Geophys Res Lett 39:L14707. doi: 10.1029/2012GL052459 CrossRefGoogle Scholar
  18. Donat MG, Leckebusch GC, Pinto JG, Ulbrich U (2010) European storminess and associated circulation weather types: future changes deduced from a multi-model ensemble of GCM simulations. Clim Res 42:27–43. doi: 10.3354/cr00853 CrossRefGoogle Scholar
  19. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107CrossRefGoogle Scholar
  20. Evans B, Lyons T (2013) Bioclimatic Extremes drive forest mortality in southwest, Western Australia. Climate 1:28–52. doi: 10.3390/cli1020028 CrossRefGoogle Scholar
  21. Evans JP, McCabe MF (2013) Effect of model resolution on a regional climate model simulation over southeast Australia. Clim Res 56:131–145. doi: 10.3354/cr01151 CrossRefGoogle Scholar
  22. Evans JP, Ekström M, Ji F (2011) Evaluating the performance of a WRF physics ensemble over South-East Australia. Clim Dyn 39(6):1241–1258. doi: 10.1007/s00382-011-1244-5 CrossRefGoogle Scholar
  23. Fasullo JT (2010) Robust land-ocean contrasts in energy and water cycle feedbacks. J Clim 23:4677–4693. doi: 10.1175/2010JCLI3451.1 CrossRefGoogle Scholar
  24. Feldmann H, Frueh B, Schaedler G, Panitz HJ, Keuler K, Jacob D, Lorenz P (2008) Evaluation of the precipitation for south-western Germany from high resolution simulations with regional climate models. Meteorologische Zeitschrift 17:455–465. doi: 10.1127/0941-2948/2008/0295 CrossRefGoogle Scholar
  25. Fischer EM, Seneviratne SI, Vidale PL, Lüthi D, Schär C (2007) Soil moisture–atmosphere interactions during the 2003 European summer heat wave. J Clim 20:5081–5099. doi: 10.1175/JCLI4288.1 CrossRefGoogle Scholar
  26. Frederiksen JS, Frederiksen CS (2007) Interdecadal changes in southern hemisphere winter storm track modes. Tellus Ser A Dyn Meteorol Oceanogr 59:599–617. doi: 10.1111/j.1600-0870.2007.00264.x CrossRefGoogle Scholar
  27. Gao Y, Fu JS, Drake JB, Liu Y, Lamarque JF (2012) Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system. Environ Res Lett. doi: 10.1088/1748-9326/7/4/044025 Google Scholar
  28. Gentilli J (1971) Climates of Australia and New Zealand. Elsevier Pub. Co., AmsterdamGoogle Scholar
  29. Gordon HB, Rotstayn LD, McGregor JL, Dix MR, Kowalczyk EA, OFarrell SP, Waterman LJ, Hirst AC, Wilson SG, Collier MA (2002) The CSIRO Mk3 climate system model, vol 130. CSIRO Atmospheric ResearchGoogle Scholar
  30. Grace W, Curran E (1993) A binormal model of frequency distributions of daily maximum temperature. Aust Met Mag 42:151–161Google Scholar
  31. Grainger S, Frederiksen CS, Zheng X (2013) Modes of interannual variability of Southern Hemisphere atmospheric circulation in CMIP3 models: assessment and projections. Clim Dyn 41:479–500. doi: 10.1007/s00382-012-1659-7 CrossRefGoogle Scholar
  32. Grell GA, Emeis S, Stockwell WR, Schoenemeyer T, Forkel R, Michalakes J, Knoche R, Seidl W (2000) Application of a multiscale, coupled MM5/chemistry model to the complex terrain of the VOTALP valley campaign. Atmos Environ 34:1435–1453CrossRefGoogle Scholar
  33. Hirsch AL, Kala J, Pitman AJ, Carouge C, Evans JP, Haverd V, Mocko D (2014) Impact of land surface initialization approach on subseasonal forecast skill: a regional analysis in the Southern Hemisphere. J Hydrometeorol 15:300–319. doi: 10.1175/JHM-D-13-05.1 CrossRefGoogle Scholar
  34. Hong SY, Dudhia J, Chen SH (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–120. doi: 10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2 CrossRefGoogle Scholar
  35. Hope P, Keay K, Pook M, Catto J, Simmonds I, Mills G, McIntosh P, Risbey J, Berry G (2014) A comparison of automated methods of front recognition for climate studies: a case study in southwest Western Australia. Mon Weather Rev 142:343–363. doi: 10.1175/MWR-D-12-00252.1 CrossRefGoogle Scholar
  36. Hughes L (2003) Climate change and Australia: trends, projections and impacts. Austral Ecol 28:423–443. doi: 10.1046/j.1442-9993.2003.01300.x CrossRefGoogle Scholar
  37. Jones DA, Wang W, Fawcett R (2009) High-quality spatial climate data-sets for Australia. Aust Meteorol Oceanogr J 58:233–248Google Scholar
  38. Kain JS (2004) The Kain-Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181CrossRefGoogle Scholar
  39. Kala J, Lyons TJ, Foster IJ, Nair US (2009) Validation of a simple steady-state forecast of minimum nocturnal temperatures. J Appl Meteorol Climatol 48:624–633. doi: 10.1175/2008JAMC1956.1 CrossRefGoogle Scholar
  40. Kala J, Andrys J, Lyons TJ, Foster IJ, Evans B (2015) Sensitivity of WRF to driving data and physics options on a seasonal time-scale for the southwest of Western Australia. Clim Dyn 44:633–659. doi: 10.1007/s00382-014-2160-2 CrossRefGoogle Scholar
  41. Kharin VV, Zwiers FW, Zhang X, Hegerl GC (2007) Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations. J Clim 20:1419–1444. doi: 10.1175/JCLI4066.1 CrossRefGoogle Scholar
  42. Leibensperger EM, Mickley LJ, Jacob DJ, Chen WT, Seinfeld JH, Nenes A, Adams PJ, Streets DG, Kumar N, Rind D (2012) Climatic effects of 1950–2050 changes in US anthropogenic aerosols-part 1: aerosol trends and radiative forcing. Atmos Chem Phys 12:3333–3348. doi: 10.5194/acp-12-3333-2012 CrossRefGoogle Scholar
  43. Malcolm JR, Liu C, Neilson RP, Hansen L, Hannah LEE (2006) Global warming and extinctions of endemic species from biodiversity hotspots. Conserv Biol 20:538–548. doi: 10.1111/j.1523-1739.2006.00364.x CrossRefGoogle Scholar
  44. Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, Gregory JM, Kitoh A, Knutti R, Murphy JM, Noda A (2007) Global climate projections. In: 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change, vol 283, chap 10. Cambridge University Press, Cambridge, pp 747–846Google Scholar
  45. Mishra V, Dominguez F, Lettenmaier DP (2012) Urban precipitation extremes: how reliable are regional climate models? Geophys Res Lett 39(L03):407. doi: 10.1029/2011GL050658 Google Scholar
  46. Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102(D):16,663–16,682. doi: 10.1029/97JD00237 CrossRefGoogle Scholar
  47. Nakićenović N, Alcamo J, Davis G, De Vries B, FenhannJ, Gaffin S, Gregory K, Grübler A, Jung T, Kram T (2000) IPCC special report on emissions scenarios (SRES), working group III, Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, CambridgeGoogle Scholar
  48. Naveau P, Guillou A, Rietsch T (2014) A non-parametric entropy-based approach to detect changes in climate extremes. J R Stat Soc 76:861–884. doi: 10.1111/rssb.12058 CrossRefGoogle Scholar
  49. O’Donnell AJ, Cook ER, Palmer JG, Turney CSM, Page GFM, Grierson PF (2015) Tree rings show recent high summer-autumn precipitation in Northwest Australia is unprecedented within the last two centuries. PloS One. doi: 10.1371/journal.pone.0128533 Google Scholar
  50. Perkins SE, Pitman AJ, Holbrook NJ, McAneney J (2007) Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J Clim 20:4356–4376. doi: 10.1175/JCLI4253.1 CrossRefGoogle Scholar
  51. Perron M, Sura P (2013) Climatology of non-Gaussian atmospheric statistics. J Clim 26:1063–1083. doi: 10.1175/JCLI-D-11-00504.1 CrossRefGoogle Scholar
  52. Persson G, Bärring L, Kjellström E (2007) Climate indices for vulnerability assessments. 111, SMHIGoogle Scholar
  53. Pielke RA, Wilby RL (2012) Regional climate downscaling: what’s the point? Eos Trans Am Geophys Union 93:52–53. doi: 10.1029/2012EO050008 CrossRefGoogle Scholar
  54. Pitts RO, Lyons TJ (1990) Airflow over a two-dimensional escarpment. II: hydrostatic flow. Q J R Meteorol Soc 116:363–378. doi: 10.1002/qj.49711649207 CrossRefGoogle Scholar
  55. Pook MJ, Risbey JS, McIntosh PC (2012) The synoptic climatology of cool-season rainfall in the central wheatbelt of Western Australia. Mon Weather Rev 140(1):28–43CrossRefGoogle Scholar
  56. Risbey JS, Pook MJ, McIntosh PC (2013) Spatial trends in synoptic rainfall in southern Australia. Geophys Res Lett 40(14):3781–3785. doi: 10.1002/grl.50739 CrossRefGoogle Scholar
  57. Roeckner E (2003) The atmospheric general circulation model ECHAM 5. Part I: model description, rep. 349, Max Planck Inst. for Meteorol., HamburgGoogle Scholar
  58. Salathé EP, Leung LR, Qian Y, Zhang Y (2010) Regional climate model projections for the state of Washington. Clim Change 102:51–75. doi: 10.1007/s10584-010-9849-y CrossRefGoogle Scholar
  59. Seidel DJ, Fu Q, Randel WJ, Reichler TJ (2008) Widening of the tropical belt in a changing climate. Nat Geosci 1:21–24. doi: 10.1038/ngeo.2007.38 Google Scholar
  60. Shukla J, DelSole T, Fennessy M, Kinter J, Paolino D (2006) Climate model fidelity and projections of climate change. Geophys Res Lett 33(L07):702. doi: 10.1029/2005GL025579 Google Scholar
  61. Smith IN, Mcintosh P, Ansell TJ, Mcinnes K (2000) Southwest Western Australian winter rainfall and its association with Indian Ocean climate variability. Int J Climatol 1930:1913–1930. doi: 10.1002/1097-0088(200012)20:15<1913:AID-JOC594>3.0.CO;2-J CrossRefGoogle Scholar
  62. Song R, Gao X, Zhang H, Moise A (2008) 20 km resolution regional climate model experiments over Australia: experimental design and simulations of current climate. Aust Meteorol Mag 57:175–193Google Scholar
  63. Stéfanon M, Drobinski P, D’Andrea F, Lebeaupin-Brossier C, Bastin S (2014) Soil moisture–temperature feedbacks at meso-scale during summer heat waves over Western Europe. Clim Dyn 42:1309–1324. doi: 10.1007/s00382-013-1794-9 CrossRefGoogle Scholar
  64. Suppiah R, Hennessy KJ, Whetton PH, Mcinnes K, Macadam I, Bathols J, Ricketts J, Page CM (2007) Australian climate change projections derived from simulations performed for the IPCC 4th assessment report. Aust Meteorol Mag 56:131–152Google Scholar
  65. Taylor KE, Stouffer RJ, Meehl Ga (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  66. Tippett MK, Kleeman R, Tang Y (2004) Measuring the potential utility of seasonal climate predictions. Geophys Res Lett 31:1–4. doi: 10.1029/2004GL021575 CrossRefGoogle Scholar
  67. Trewin BC (2001) Extreme temperature events in Australia. Submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy, October 2001. School of Earth Sciences, The University of MelbourneGoogle Scholar
  68. Turner NC, Asseng S (2005) Productivity, sustainability, and rainfall-use efficiency in Australian rainfed Mediterranean agricultural systems. Crop Pasture Sci 56:1123–1136. doi: 10.1071/AR05076 CrossRefGoogle Scholar
  69. Webb LB, Watterson I, Bhend J, Whetton PH, Barlow EWR (2013) Global climate analogues for winegrowing regions in future periods: projections of temperature and precipitation. Aust J Grape Wine Res 19:331–341. doi: 10.1111/ajgw.12045 CrossRefGoogle Scholar
  70. Wehner M, Smith R, Bala G, Duffy P (2010) The effect of horizontal resolution on simulation of very extreme US precipitation events in a global atmosphere model. Clim Dyn 34:241–247. doi: 10.1007/s00382-009-0656-y CrossRefGoogle Scholar
  71. Wright PB (1974) Seasonal rainfall in Southwestern Australia and the general circulation. Mon Weather Rev 102:219–232CrossRefGoogle Scholar
  72. Xue Y, Janjic Z, Dudhia J, Vasic R, De Sales F (2014) A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability. Atmos Res 147–148:68–85. doi: 10.1016/j.atmosres.2014.05.001 CrossRefGoogle Scholar
  73. Ylhaisi JS, Raisanen J (2013) Twenty-first century changes in daily temperature variability in CMIP3 climate models. Int J Climatol 1428:1414–1428. doi: 10.1002/joc.3773 Google Scholar
  74. Zheng B, Chenu K, Fernanda Dreccer M, Chapman SC (2012) Breeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat (Triticum aestivium) varieties? Glob Change Biol 18:2899–2914. doi: 10.1111/j.1365-2486.2012.02724.x CrossRefGoogle Scholar
  75. Zwiers FW, von Storch H (1995) Taking serial correlation into account in tests of the mean. J Clim 8:336–351. doi: 10.1175/1520-0442(1995)008<0336:TSCIAI>2.0.CO;2 CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Environmental and Conservation Sciences, School of Veterinary and Life SciencesMurdoch University MurdochPerthAustralia
  2. 2.Australian Research Council Center of Excellence for Climate Systems ScienceSydneyAustralia

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