| Summary: | In this paper, we investigate the impact of historical land cover change on climate extremes in eastern Australia by analysing data from an ensemble of model simulations using CSIRO AGCM. The model simulations were performed for two sets of prescribed land surface parameters representative of pre- European and modern-day land cover conditions. To evaluate the impact of historical land cover change on Australian regional climate, the CSIRO AGCM was used to complete two sets of model simulations (ensemble of 10 each) for the period 1951-2003. In this study, we used the CSIRO climate model consisting of atmospheric and land surface components forced by observed sea surface temperature and sea ice data for the period 1951-2003 (Rayner et al., 1996). This experimental set-up followed the design of the Climate of the 20th Century project (Folland et al., 2002) and allows for direct comparison between observed and model simulated ENSO events which are known to strongly influence Australian climate. The only difference between the experiments was the land surface characteristics for Australian continent used by the CSIRO model. The first set of model simulations used the modern-day and the second used the pre-European land cover characteristics. Outside Australia, the land cover characteristics were set at modern day conditions for both experiments. The modern-day land surface conditions were derived using data from the AVHRR satellite imagery for the period 1981 to 2001 at an 8km spatial footprint (Lawrence, 2004). The monthly long-term average values of vegetation cover class, leaf area index, vegetation fraction and surface albedo were used as an input to the Simple Biosphere Model (SiB) derivation methods described in Sellers et al.(1986) to compute land surface characteristics used by the CSIRO climate model. Pre-clearing land surface parameters of vegetation fraction, leaf area index, surface albedo and stomatal resistance were generated by extrapolating the modern-day monthly values of remnant native vegetation ...
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