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The development of a high quality historical temperature data base for Australia

A high quality, historical surface air temperature data set is essential for the reliable investigation of climate change and variability. In this study, such a data set has been prepared for Australia by adjusting raw mean annual temperature data for inhomogeneities associated with station relocations, changes in exposure, and other problems. Temperature records from long-term stations were collaborated from the set of all raw data held by the Australian Bureau of Meteorology. These long-term records were extended by combining stations and manually entering previously unused archived temperature measurements. An objective procedure was developed to determine the necessary adjustments, in conjunction with complementary statistical methods and station history documentation. The objective procedure involved creating a reference time series for each long-term station, from the median values at surrounding, well-correlated stations. Time series of annual mean maximum and mean minimum temperatures have been produced for 224 stations, and the adjusted dataset has been made available to the research community. The adjusted data are likely to be more representative of real climatic variations than raw data due to the removal of discontinuities. The adjusted data set has been compared with previously used temperature data sets, and data sets of other parameters. The adjusted data set provides adequate spatial coverage of Australia back to 1910. Additional adjusted data are available prior to this date at many stations. Trends in annual mean maximum, minimum, the mean of the maximum and minimum, and the range between the maximum and minimum, have been calculated at each site. Maximum and minimum temperatures have increased since about 1950, with minimum temperatures increasing faster than maximum temperatures.

Identiferoai:union.ndltd.org:ADTP/279001
Date January 1996
CreatorsTorok, Simon James
Source SetsAustraliasian Digital Theses Program
Detected LanguageEnglish
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