Estimating the potential predictability of Western Australian surface temperature using monthly data

Simon Grainger, Carsten S Frederiksen, Xiaogu Zheng

Abstract


The seasonal mean of a climate variable is considered to be a statistical random variable with two components: a slow component related to slowly varying (time scales of a season or more) forcings from external and internal atmospheric sources, and an intraseasonal component related to forcings from weather variability with time scales less than a season. Here, an extension of a previous Analysis of Variance method is proposed which deals with climate data in all seasons when estimating the intraseasonal variability. By removing this from the total variability, an estimate for the slow component, and hence the long range predictability, of the seasonal mean is made. The method is applied to monthly surface temperature data for Western Australia from 1951--2000.

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DOI: http://dx.doi.org/10.21914/anziamj.v50i0.1414



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