Summary1. Gridded climatologies have become an indispensable component of bioclimatic modelling, with a range of applications spanning conservation and pest management. Such globally conformal data sets of historical and future scenario climate surfaces are required to model species potential ranges under current and future climate scenarios. 2. We developed a set of interpolated climate surfaces at 10¢ and 30¢ resolution for global land areas excluding Antarctica. Input data for the baseline climatology were gathered from the WorldClim and CRU CL1AE0 and CL2AE0 data sets. A set of future climate scenarios were generated at 10¢ resolution. For each of the historical and future scenario data sets, the full set of 35 Bioclim variables was generated. Climate variables (including relative humidity at 0900 and 1500 hours) were also generated in CLIMEX format. The Ko¨ppen-Geiger climate classification scheme was applied to the 10¢ hybrid climatology as a tool for visualizing climatic patterns and as an aid for specifying absence or background data for correlative modelling applications. 3. We tested the data set using a correlative model (MaxEnt) addressing conservation biology concerns for a rare Australian shrub, and a mechanistic niche model (CLIMEX) to map climate suitability for two invasive species. In all cases, the underlying climatology appeared to behave in a robust manner. 4. This global climate data set has the advantage over the WorldClim data set of including humidity data and an additional 16 Bioclim variables. Compared with the CRU CL2AE0 data set, the hybrid 10¢ data set includes improved precipitation estimates as well as projected climate for two global climate models running relevant greenhouse gas emission scenarios. 5. For many bioclimatic modelling purposes, there is an operational attraction to having a globally conformal historical climatology and future climate scenarios for the assessments of potential climate change impacts. Our data set is known as 'CliMond' and is available for free download from http://www.climond.org.

We examined the effects of past and future climate change on natural snow cover in southeastern mainland Australia and assessed the role of snowmaking in adapting to projected changes in snow conditions. Snow-depth data from 4 alpine sites from 1957 to 2002 indicated a weak decline in maximum snow depths at 3 sites and a moderate decline in mid-to late-season snow depths (August to September). Low-impact and high-impact climate change scenarios were prepared for 2020 and 2050 and used as input for a climate-driven snow model. The total area with an average of at least 1 d of snow cover per year was projected to decrease by 10 to 39% by 2020, and by 22 to 85% by 2050. By 2020, the length of the ski season was projected to have decreased by 10 to 60%, while by 2050 the decrease was 15 to 99%. Based on target snow-depth profiles from May to September nominated by snowmaking managers at various ski resorts, the snow model simulated the amount of snow that is needed to be made each day, taking into account natural snowfall, snow-melt and the pre-existing natural snow depth. By the year 2020, an increase of 11 to 27% in the number of snow guns would be required for the low impact scenario, and 71 to 200% for the high impact scenario. This corresponds to changes in total snow volume of 5 to 17% for the low impact scenario to 23 to 62% for the high impact scenario. Therefore, with sufficient investment in snow guns, the Australian ski industry may be able to manage the effect of projected climate change on snow cover until at least 2020.KEY WORDS: Snow · Depth · Area · Duration · Australia · Climate · Change · Snowmaking Resale or republication not permitted without written consent of the publisherClim Res 35: [255][256][257][258][259][260][261][262][263][264][265][266][267][268][269][270] 2008 annual snow-cover extent since 1966, largely due to decreases in spring and summer snow cover since the mid-1980s over both the Eurasian and American continents (Robinson & Frei 2000). Surface observations for the northern hemisphere from show no significant change in winter snow extent, but a decrease in spring (Brown 2000). At most locations below 1800 m in northwestern USA, large decreases in waterequivalent snow depth from 1950-2000 coincide with significant increases in temperature, despite increases in precipitation (Groisman et al. 2004, Mote et al. 2005. Since the late 1940s, there has been a shift toward earlier snow-melt runoff in many rivers of northwestern America (Stewart et al. 2005).In the Australian region, there has been a warming of 0.9°C since 1900, most of which has occurred since 1950 (Nicholls & Collins 2006). Australian rainfall exhibits large annual and regional variability, including a decline in annual rainfall in the east since 1950 (Nicholls & Collins, 2006). Climate trends are likely to have had an effect on the Australian snowfields, but the large annual variability in snow season characteristics in the mainland Australian alpine region makes it difficult to detect trends. Fig. 1 shows ...

Changes in wind due to global warming may have large geophysical and societal impacts. The 10 m winds from the Coupled Model Intercomparison Project Phase 3 multi-model ensemble are assessed against reanalysis winds and found to exhibit lowest skill over land areas. Maps of future change in mean wind speed, direction and 99th percentile wind speed are presented to convey spatial information as well as the multi-model agreement on sign and magnitude of the change. The utility of these maps in providing context for the design of more detailed impact studies, for which wind is a required input, is discussed.

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The subtropical ridge (STR) is the mean pressure ridge in the mid-latitudes, and is one of the key features affecting climate variability and change in southeast Australia. Changes to the STR and associated changes to rainfall in a warming climate are of strong interest, and the new Coupled Model Inter-comparison Project phase 5 (CMIP5) model archive provides new opportunities to examine this. Here we show that the STR is projected to strengthen and move pole-ward under global warming, contributing to reduced rainfall in the cool season in southeast Australia. This result is largely consistent among 35 models examined, and CMIP5 shows a greater increase in intensity relative to position than CMIP3 did. We show that the simulation of the STR in the CMIP5 is similar to that of the previous CMIP3 in many respects, including the underestimation of both the historical trends in the STR intensity and the correlation between inter-annual STR intensity and southeast Australian rainfall. These issues mean we still have reduced confidence in regional rainfall projections for southeast Australia and suggest that CMIP5 rainfall projections for this region in April to October may be underestimates.