Assessing rainfall trends and remote drivers in regional climate change projections: The demanding test case of Tasmania

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1 IOP Conference Series: Earth and Environmental Science Assessing rainfall trends and remote drivers in regional climate change projections: The demanding test case of Tasmania To cite this article: M R Grose et al 2010 IOP Conf. Ser.: Earth Environ. Sci Related content - Improved regional climate modelling through dynamical downscaling Stuart Corney, Jack Katzfey, John McGregor et al. - Rainfall declines over Queensland from and links to the Subtropical Ridge and the SAM D A Cottrill and J Ribbe - East coast lows, atmospheric blocking and rainfall: A Tasmanian perspective Michael Pook, James Risbey and Peter McIntosh View the article online for updates and enhancements. This content was downloaded from IP address on 15/07/2018 at 11:45

2 17th National Conference of the Australian Meteorological and Oceanographic Society IOP Publishing IOP Conf. Series: Earth and Environmental Science 11 (2010) doi: / /11/1/ Assessing rainfall trends and remote drivers in regional climate change projections: the demanding test case of Tasmania MR Grose 1, S Corney 1, J Bennett 2, CJ White 1, GK Holz 1 and NL Bindoff 1,3 1 Climate Futures for Tasmania, Antarctic Climate and Ecosystems Co-operative Research Centre, University of Tasmania, Private Bag 80, Hobart, TAS 7001, Australia 2 Hydro Tasmania Consulting, 89 Cambridge Park Drive, Cambridge, TAS 7170, Australia 3 Centre for Australian Weather and Climate Research, Aspendale, VIC 3195, Australia Michael.Grose@acecrc.org.au Abstract. Understanding and modelling Tasmanian rainfall variability and making future projections of Tasmanian rainfall are challenging tasks. Tasmania has spatially and temporally complex rainfall patterns. Rainfall variability is influenced by a complex suite of remote drivers and these influences vary by season. The Climate Futures for Tasmania high-resolution model simulations project small changes to annual rainfall averaged over Tasmania, but larger changes to the spatial patterns and seasonality of rainfall. A case study of changes to summer rainfall under a high greenhouse gas emission scenario is shown here. The projected summer decrease in rainfall in the western rainfall region is consistent with the southerly movement and intensification of the subtropical ridge as well as an enhancement of the high phase of the Southern Annular Mode. The increase along the east coastal strip is consistent with an increase in blocking in the Tasman Sea as well as an increase in sea surface temperature, relative humidity and convective rainfall. We propose that projections of rainfall for places like Tasmania are strengthened through dynamical downscaling and also the analysis of the rainfall mechanisms within the model at all length scales. 1. Introduction Tasmania is an island with a temperate maritime climate that lies between 39.5 and 44 S in the Roaring 40s belt of westerly airflow. The interaction of the westerlies with rugged topography leads to a strong pattern of rainfall variability across Tasmania, with over 3000 mm falling per annum near the west coast and approximately 600 mm per annum in the central midlands. The westerlies are weakest in summer. Westerly flow can be interrupted in any season by blocking highs in the Tasman Sea [1] and these blocks are associated with cutoff lows that can cause high rainfall events in the northeast [2]. The seasonality of rainfall varies in different regions of the state, with a distinct seasonal cycle in the western region, and no significant cycle in the east. Tasmanian rainfall variability is influenced by various remote drivers, including the El Niño Southern Oscillation (ENSO), Southern Annular Mode (SAM), Indian Ocean Dipole (IOD) and atmospheric blocking in the Tasman Sea. The strength of the influence of these drivers varies across c 2010 IOP Publishing Ltd 1

3 17th National Conference of the Australian Meteorological and Oceanographic Society IOP Publishing IOP Conf. Series: Earth and Environmental Science 11 (2010) doi: / /11/1/ the state and in different seasons. In summer, rainfall variability shows the greatest correlation with an index of SAM on the west coast and an index of blocking on the east coast [3]. 2. Climate modelling: methods Output from six global climate models (GCMs) were dynamically downscaled to a fine resolution appropriate to Tasmania using the CSIRO Conformal Cubic Atmospheric Model (CCAM) [4]. This dynamical downscaling method takes output from a host GCM and uses it as forcing into a stretched grid global atmospheric model. The result is a fine-scale dynamical model over the area of interest. To achieve a desired final resolution of 0.1, a two stage downscaling process was implemented. The first stage (intermediate model) downscaled host GCM outputs to a grid with the high-resolution face of the grid covering all of Australia at a resolution of approximately 0.5. The second stage placed the high-resolution face over Tasmania and the Bass Strait islands at an approximate resolution of 0.1. The representation of the average annual total rainfall for the baseline climatology period of is improved through both of the downscaling stages (figure 1). A typical GCM resolution (left panel) only has a few grid cells that cover the state, suggesting the average state-wide annual total precipitation is approximately 750 mm. The 0.5 resolution model (centre panel) shows greater spatial structure and an average total of approximately 1000 mm. The final 0.1 resolution model (right panel) has a finely resolved spatial pattern of rainfall and an average total of 1385 mm, closely resembling the observed spatial patterns and total of 1390 mm measured by the Bureau of Meteorology [5]. It was concluded that the high-resolution 0.1 dynamical downscaling process had the ability to model the present climate of Tasmania with a high degree of fidelity, including seasonality, spatial variance and relationships between the different climate variables [6]. Typical GCM projection 0.5 model projection 0.1 model projection Figure 1. Average annual precipitation totals for Tasmania projected on typical GCM, 0.5 and 0.1 grids. Precipitation scaled from mm per annum Six GCMs were selected based on an assessment of their reproduction of present-day climate of eastern Australia [7]. The GCMs selected were CSIRO-Mk3.5 (Australia), GFDL-CM2.0 and GFDL- CM2.1 (USA), ECHAM5/MPI-OM (Germany), UKMO-HadCM3 (UK), and MIROC3.2(medres) (Japan). Two SRES emission scenarios were used to provide a range of likely projected futures, from a low (B1) to a high (A2) emission of greenhouse gases. For the purposes of this brief paper the sixmodel mean for all analyses is presented. Rainfall changes over Tasmania are examined in the finest scale model outputs (0.1 grid) and changes to large-scale drivers are examined in the intermediate resolution model simulations (0.5 grid). 3. Results The six-model mean of the projections shows a change of less than 5% in total annual rainfall under either emission scenario and larger changes of up to 15% on a seasonal basis. Individual districts within Tasmania show much larger changes than the statewide average. It should be noted that the 2

4 17th National Conference of the Australian Meteorological and Oceanographic Society IOP Publishing IOP Conf. Series: Earth and Environmental Science 11 (2010) doi: / /11/1/ Tasmanian rainfall average is dominated by the high rainfall region of the west coast. The projections under the two scenarios show a similar spatial pattern of change, but there is an enhancement of the magnitude of the change in the higher emission scenario is observed compared to the lower. Summer rainfall under the A2 scenario shows a steadily emerging pattern of increased rainfall in the east and northeast areas of Tasmania and a decrease in summer rainfall on the west and southwest regions (figure 2). Figure 2. Projection of six-model-mean Tasmanian summer rainfall for the A2 scenario, a) 11year moving average timeseries of proportional rainfall anomaly from baseline for Tasmania and three Bureau of Meteorology forecast zones (East = East Coast, Central = Central Plateau & Upper Derwent Valley, West = West & South Coast & Highlands ), b) map of proportional difference in summer rainfall between the periods marked on the timeseries plot (1 = , 2 = , 3 = , 4 = ) The six-model mean of selected indices of relevance to the climate variability of Tasmania is shown in figure 3. An index of the summer intensity of the subtropical ridge (STR) [8] is seen to increase by 1 hpa over the projections. An index of the position of the STR [9] shows a southerly shift of >1 degree in summer. The blocking index at 140 E [10] shows a steady increase over the period and the regional Antarctic Oscillation Index [11] shows a steady intensification of the Summer SAM. These all appear as a continuation of the current direction of trend as indicated by anomaly values from NCEP Reanalysis 1 [12] also shown on the plots. 3

5 17th National Conference of the Australian Meteorological and Oceanographic Society IOP Publishing IOP Conf. Series: Earth and Environmental Science 11 (2010) doi: / /11/1/ Figure 3. Timeseries of climate indices anomaly from mean calculated from NCEP Reanalysis and the six-model-mean, a) summer central pressure (intensity) of the subtropical ridge across the Australian zone, b) summer latitude anomaly of the subtropical ridge, c) summer blocking index anomaly at 140 E, d) summer regional Antarctic Oscillation Index anomaly Changes to summer mean sea level pressure (MSLP), zonal wind and sea surface temperature (SST) are shown in figure 4. Maps indicate the modelled mean for the recent period ( ) and the change between the recent period and the end of the century ( ). There is an increase in summer MSLP in the region of Tasmania. The increase is greater over New Zealand to the east and in the Indian Ocean to the west. Zonal wind is strongly positive (westerly wind) in the latitude of Tasmania. The average strength of the westerlies is seen to decrease by approximately 1 ms-1 in the region of Tasmania in these projections. Summer SST shows a current gradient from >17 C in the northeast to <15 C in the southwest. This gradient is seen to increase in these projections, with an increase in summer SST of >3 C on the east coast and <2.3 C on the west coast. This is likely to be due to a strengthening or increased extension of the East Australia Current. 4

6 17th National Conference of the Australian Meteorological and Oceanographic Society IOP Publishing IOP Conf. Series: Earth and Environmental Science 11 (2010) doi: / /11/1/ Figure 4. Maps showing the average mean sea level pressure (MSLP), zonal wind and sea surface temperature (SST) present in the models in summer , and the change in these means to There is an east-west pattern in variables related to rainfall and heat balance (not shown). Over the eastern strip there is an increase in cloud cover, a reduction in solar radiation and an increase in relative humidity whereas the western district experiences a decrease in cloud cover, an increase in solar radiation and a decrease in relative humidity. There is an increase in convective available potential energy (CAPE) over the entire state, but the increase is greater over the eastern region. Similarly, there is a general increase in the proportion of rainfall that falls through convective processes and this change is greater on the eastern side. There is an increase in the maximum precipitation rate over the eastern strip and a decrease over the west. 5

7 17th National Conference of the Australian Meteorological and Oceanographic Society IOP Publishing IOP Conf. Series: Earth and Environmental Science 11 (2010) doi: / /11/1/ Discussion and Conclusion The changes to mean summer rainfall shown in figure 2 can be related coherently to the changes in the climate drivers shown in figures 3 and 4. The decrease in rainfall on the west coast is consistent with the weakening and deflection of westerly systems at the latitude of Tasmania indicated by the intensification and southerly movement of the STR and a decrease in the dominant zonal wind. The increase in the SAM index is also consistent with a rainfall decline. In contrast, the rainfall increase seen in the northeast strip is consistent with the increase in blocking index and a change to the mean zonal wind, which implies an increase in northeasterly rain-bearing systems including cutoff lows. The increase is also consistent with an increase in SST, CAPE, convective processes and rainfall intensity indicating an increase in dynamic precipitation events. Tasmanian rainfall distribution is reliant on a complex suite of mechanisms and drivers at all scales, and an interaction of systems with complex topography. Fine scale model simulations appear more able to account for all the relevant drivers at all scales, including the interaction of air with topography than the corresponding coarse scale GCMs. Also, the projections of rainfall can be used with more confidence when the drivers behind rainfall changes are examined, and the projected changes are plausible and are consistent with our knowledge of climate dynamics. Acknowledgements This work was supported by the Australian Government s Cooperative Research Centre Programme through the Antarctic Climate and Ecosystems Cooperative Research Centre (ACE CRC). Climate Futures for Tasmania is possible with support through funding and research of a consortium of state and national partners. References [1] Sturman A and Tapper N 1996 The weather and climate of Australia and New Zealand. (Melbourne, Vic: Oxford University Press) [2] Pook MJ, Risbey JS and McIntosh PC IOP Conf. Ser. : Earth. Environ. Sci. this volume [3] Risbey JS, Pook MJ, McIntosh PC, Wheeler MC and Hendon HH 2009 Mon. Weath. Rev [4] McGregor JL 2005 CCAM: geometric aspects and dynamical formulation Tech. Paper 70 (Melbourne, Vic: CSIRO Marine and Atmospheric) [5] Jones DA, Wang W and Fawcett R 2009 Aust. Met. & Oceanog. J [6] Corney S, Katzfey JJ, McGregor JL, Grose MR, Bennett J, White CJ, Holz GK and Bindoff NL In Press ACE CRC report, Hobart Tasmania [7] Smith IN and Chandler E 2009 Clim. Change. DOI /s [8] Larsen SH and Nicholls N 2009 Geophys. Res. Lett. 36 L08708 [9] Drosdowsky W 2005 Int. J. of Climatol [10] Pook MJ and Gibson TT 1999 Aust. Met. Mag [11] Meneghini B, Simmonds I and Smith IN 2007 Int. J. of Climatol [12] Kalnay E et al Bull. Am. Met. Soc