A new homogenized daily maximum and minimum temperature data set, the Australian Climate Observations Reference Network—Surface Air Temperature data set, has been developed for Australia. This data set contains data from 112 locations across Australia, and extends from 1910 to the present, with 60 locations having data for the full post-1910 period.
These data have been comprehensively analysed for inhomogeneities and data errors ensuring a set of station temperature data which are suitable for the analysis of climate variability and trends. For the purposes of merging station series and correcting inhomogeneities, the data set has been developed using a technique, the percentile-matching (PM) algorithm, which applies differing adjustments to daily data depending on their position in the frequency distribution. This method is intended to produce data sets that are homogeneous for higher-order statistical properties, such as variance and the frequency of extremes, as well as for mean values. The PM algorithm is evaluated and found to have clear advantages over adjustments based on monthly means, particularly in the homogenization of temperature extremes. Copyright © 2012 Royal Meteorological Society
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