ALBERT

Notes: The distribution and area of temporary wetlands across the arid zone of Australia are highly variable. Any change in their distribution or extent due to climate change and/or extraction of water has the potential to adversely impact dependent biota. Satellite imagery was used to determine the spatial and temporal distribution of wetlands across arid Australia over an 11-year period. Synoptic climate data were examined to identify the weather systems that caused wetland filling events. Simple threshold models relating rainfall to wetland filling for seven large regions of Australia were developed to examine patterns of wetland filling over the last 100 years. These data were used to examine the climatic processes that drive wetland filling and the likely impacts of climate change on wetland distribution. The strongest climatic influence on wetland filling in the arid zone was tropical weather systems. Their influence extended into southern regions and their effects were often widespread. Variation in wetland area in all regions of the arid zone was high. The Lake Eyre Basin experienced more large flood events than other regions and had the most large, persistent wetlands that remain unregulated by humans. Hindcasting of past filling events indicated that there was a general pattern of frequent wetland filling across inland Australia in the 1910s, 1950s and 1970s, and less frequent wetland filling in the late 1920s, 1930s and 1960s. Furthermore, there appeared to be no period greater than 12 months over the previous 95 years when there was no predicted wetland filling in the arid zone. Wetland ecosystems dependent on a few infrequent heavy rainfalls are clearly vulnerable to any change in frequency or magnitude of these events. Climate change that results in a drying or reduced frequency of large flood events, exacerbated by extraction of water for agriculture, could be catastrophic for some biota, particularly waterbirds, which use a mosaic of wetland habitat at broad spatial scales.

Notes: Abstract In this study we present rainfall results from equilibrium 1 ×− and 2 × CO2 experiments with the CSIRO 4-level general circulation model. The 1 × CO2 results are discussed in relation to observed climate. Discussion of the 2 × CO2 results focuses upon changes in convective and non-convective rainfall as simulated in the model, and the consequences these changes have for simulated daily rainfall intensity and the frequency of heavy rainfall events. In doing this analysis, we recognize the significant shortcomings of GCM simulations of precipitation processes. However, because of the potential significance of any changes in heavy rainfall events as a result of the enhanced greenhouse effect, we believe a first examination of relevant GCM rainfall results is warranted. Generally, the model results show a marked increase in rainfall originating from penetrative convection and, in the mid-latitudes, a decline in largescale (non-convective) rainfall. It is argued that these changes in rainfall type are a consequence of the increased moisture holding capacity of the warmer atmosphere simulated for 2 × CO2 conditions. Related to changes in rainfall type, rainfall intensity (rain per rain day) increases in the model for most regions of the globe. Increases extend even to regions where total rainfall decreases. Indeed, the greater intensity of daily rainfall is a much clearer response of the model to increased greenhouse gases than the changes in total rainfall. We also find a decrease in the number of rainy days in the middle latitudes of both the Northern and Southern Hemispheres. To further elucidate these results daily rainfall frequency distributions are examined globally and for four selected regions of interest. In all regions the frequency of high rainfall events increases, and the return period of such events decreases markedly. If realistic, the findings have potentially serious practical implications in terms of an increased frequency and severity of floods in most regions. However, we discuss various important sources of uncertainty in the results presented, and indicate the need for rainfall intensity results to be examined in enhanced greenhouse experiments with other GCMs.

Notes: Abstract Potential impacts of climate change on heavy rainfall events and flooding in the Australian region are explored using the results of a general circulation model (GCM) run in an equilibrium enhanced greenhouse experiment. In the doubled CO2 simulation, the model simulates an increase in the frequency of high-rainfall events and a decrease in the frequency of low-rainfall events. This result applies over most of Australia, is statistically more significant than simulated changes in total rainfall, and is supported by theoretical considerations. We show that this result implies decreased return periods for heavy rainfall events. The further implication is that flooding could increase, although we discuss here the many difficulties associated with assessing in quantitative terms the significance of the modelling results for the real world. The second part of the paper assesses the implications of climate change for drought occurrence in Australia. This is undertaken using an off-line soil water balance model driven by observed time series of rainfall and potential evaporation to determine the sensitivity of the soil water regime to changes in rainfall and temperature, and hence potential evaporation. Potential impacts are assessed at nine sites, representing a range of climate regimes and possible climate futures, by linking this sensitivity analysis with scenarios of regional climate change, derived from analysis of enhanced greenhouse experiment results from five GCMs. Results indicate that significant drying may be limited to the south of Australia. However, because the direction of change in terms of the soil water regime is uncertain at all sites and for all seasons, there is no basis for statements about how drought potential may change.

Notes: Abstract A rainfall-runoff model (IHACRES) is applied on a daily timestep to a large area of the state of Victoria, Australia. Successful calibrations of this dynamic lumped parameter model were performed for 5 rivers contributing streamflow to the Ovens Basin, and for 9 rivers of the Goulburn Basin. This is the first application of the model on such a scale, involving two basins where the total drainage area of the catchments modelled is about 6,500 km2. The models were tested by simulation over the entire common period of observation for the 14 catchments under consideration. The results show that the models closely simulate the observed streamflow. The effect of historical climate variability on streamflow was investigated. The models were used for estimation of the potential impact of climatic change on water availability for irrigation for different climate scenarios developed in the Division of Atmospheric Research, CSIRO. This allows conditional estimates to be made of water supply in these basins for the periods 2030 and 2070 under current vegetation conditions. Projecting the future hydrologic regime in this region is extremely important, in particular for supporting irrigation management of the Basin. The problem of estimating the impact of climate change on the probability of extreme events of the hydrological regime was analysed. Flood frequency was found to increase for the scenarios providing the maximum amount of water; to 50% at 2030 and 100% at 2070. The probability of flood events for the ‘dry’ scenarios rapidly decreases for these dates. Drought frequency, as defined by a soil wetness index, increased 35% for the ‘dry’ scenario at 2030 and 80% for this scenario at 2070.

Notes: Abstract This study uses a model of snow-cover duration, an observed climate data set for the Australian alpine area, and a set of regional climate-change scenarios to assess quantitatively how changes in climate may affect snow cover in the Australian Alps. To begin, a regional interannual climate data set of high spatial resolution is prepared for input to the snow model and the resulting simulated interannual and spatial variations in snow-cover duration are assessed and compared with observations. The model provides a reasonable simulation of the sensitivities of snow-cover duration to changes in temperature and precipitation in the Australian Alps, although its performance is poorer at sites highly marginal for snow cover. (In a separate comparison, the model also performs well for sites in the European Alps.) The input climate data are then modified in line with scenarios of regional climate change based on the results of five global climate models run in enhanced greenhouse experiments. The scenarios are for the years 2030 and 2070 and allow for uncertainty associated with projecting future emissions of greenhouse gases and with estimating the sensitivity of the global climate system to enhanced greenhouse forcing. Attention focuses on the climate changes most favourable (‘best-case scenario’) and least favourable (‘worst-case scenario’) for snow cover amongst the range of climate changes in the scenarios. Under the best case scenario for 2030, simulated average snow-cover duration and the frequency of years of more than 60 days cover decline at all sites considered. However, at the higher sites (e.g., more than 1700 m) the effect is not very marked. For the worst case scenario, a much more dramatic decline in snow conditions is simulated. At higher sites, simulated average snow cover duration roughly halves by 2030 and approaches zero by 2070. At lower sites (around 1400 m), near zero average values are simulated by 2030 (compared to durations of around 60 days for current climate). These simulated changes, ranging between the best and worst case, are likely to be indicative of how climate change will affect natural snow-cover duration in the Australian Alps. However, note that the model does not allow directly for changes in the frequency and intensity of snow-bearing circulation systems, nor do the climate-change scenarios allow possible changes in interannual variability (particularly that due to the El Niño-Southern Oscillation) and local topographical effects not resolved by global climate models. The simulated changes in snow cover are worthy of further consideration in terms of their implications for the ski industry and tourism, water resources and hydroelectric power, and land-use management and planning.