A selection of 9s gridded climate change variables for continental Australia for biodiversity modelling: 1990, 2050, 2070, 2090; GFDL and ACCESS1.0; RCP 4.5, 8.5

A selection of 9sec gridded National climate change variables for biodiversity modelling. This collection represents 30-year averages centred on each of 1990, 2050, 2070, 2090. Projected future climates were generated by applying within-model changes for two circulation model outputs: GFDL and ACCESS1.0; and for two representative concentration pathways (RCP 4.5, 8.5), calculated at the native general circulation model grid resolution to these current surfaces, using ANUCLIM 6.1 prior to radiative adjustment. That the maximum temperature variables have been adjusted for topographic slope/aspect and shading effects. A short methods summary is provided in the file 9sClimateMethodsSummary.pdf for further information, including a nomenclature for files. The selected climate variables provided in this collection are: \nTNM - mean annual minimum temperature \nTXM - mean annual maximum temperature \nTXX - mean maximum monthly maximum temperature \nTXI - mean minimum monthly maximum temperature \nTNI - mean minimum monthly minimum temperature\nTNX - mean maximum monthly minimum temperature\nPTA - Average total annual rainfall\nPTX - mean maximum monthly rainfall\nPTI - mean minimum monthly rainfall\nOther variables (evaporation and water balance, temperature range, and seasonality, etc) are available upon application. The data are provided in ESRI binary float grid format (*.hdr, *.flt), Projection is geographic GDA94. \nLineage: Climate surfaces for the present were based on the ANUCLIM 6.1 (Xu and Hutchinson, 2011) 30 year average climate surfaces for Australia (1976-2005), with elevational lapse rate correction applied over the 9s GEODATA digital elevation model (Hutchinson et al , 2008). Radiative correction derived from the same DEM was applied to radiation and maximum temperature before calculation of evaporation, using the CSIRO TerraFormer software. Summary statistics for each variable were then calculated including variables described in Williams et al (2012: Which environmental variables should I use in my biodiversity model? International Journal of Geographic Information Sciences 26(11), 2009-2047. DOI: 10.1080/13658816.2012.698015.). \nDetails are given in the short summary report by Tom Harwood, Noboru Ota, Justin Perry, Kristen Williams, Ian Harman, Simon Ferrier (2014) gridded continental climate variables for Australia: November 2014. CSIRO Land and Water, Canberra. Attached with the collection. \nKey published references: \nReside AE, VanDerWal J, Phillips B, Shoo L, Rosauer D, Anderson BA, Welbergen J, Moritz C, Ferrier S, Harwood TD, Williams KJ, Mackey B, Hugh S and Williams SE (2013) Climate change refugia for terrestrial biodiversity: Defining areas that promote species persistence and ecosystem resilience in the face of global climate change. National Climate Change Adaptation Research Facility, Griffith University, Gold Coast, Qld.\nXu T and Hutchinson MF (2013) New developments and applications in the ANUCLIM spatial climatic and bioclimatic modelling package. Environmental Modelling & Software 40(0), 267-279. DOI: http://dx.doi.org/10.1016/j.envsoft.2012.10.003.\nACCESS: Bi D, Dix M, Marsland SJ, O’Farrell S, Rashid HA, Uotila P, Hirst AC, Kowalczyk E, Golebiewski M, Sullivan A, Yan H, Hannah N, Franklin C, Sun Z, Vohralik P, Watterson I, Zhou X, Fiedler R, Collier M, Ma Y, Noonan J, Stevens L, Uhe P, Zhu H, Griffies SM, Hill R, Harris C and Puri K (2013) The ACCESS coupled model: description, control climate and evaluation. Australian Meteorological and Oceanographic Journal 63(1), 41-64. \nGFDL: Dunne JP, John JG, Shevliakova E, Stouffer RJ, Krasting JP, Malyshev SL, Milly PCD, Sentman LT, Adcroft AJ, Cooke W, Dunne KA, Griffies SM, Hallberg RW, Harrison MJ, Levy H, Wittenberg AT, Phillips PJ and Zadeh N (2013) GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: Carbon system formulation and baseline simulation characteristics. Journal of Climate 26(7), 2247-2267. DOI: 10.1175/JCLI-D-12-00150.1.