A high-quality monthly total cloud amount dataset for Australia

A high-quality monthly total cloud amount dataset for 165 stations has been developed for monitoring and assessing long-term trends in cloud cover over Australia. The dataset is based on visual 9 a.m. and 3 p.m. observations of total cloud amount, with most records starting around 1957. The quality control process involved examination of historical station metadata, together with an objective statistical test comparing candidate and reference cloud series. Individual cloud series were also compared against rainfall and diurnal temperature range series from the same site, and individual cloud series from neighboring sites. Adjustments for inhomogeneities caused by relocations and changes in observers were applied, as well as adjustments for biases caused by the shift to daylight saving time in the summer months. Analysis of these data reveals that the Australian mean annual total cloud amount is characterised by high year-to-year variability and shows a weak, statistically non-significant increase over the 1957–2007 period. A more pronounced, but also non-significant, decrease from 1977 to 2007 is evident. A strong positive correlation is found between all-Australian averages of cloud amount and rainfall, while a strong negative correlation is found between mean cloud amount and diurnal temperature range. Patterns of annual and seasonal trends in cloud amount are in general agreement with rainfall changes across Australia, however the high-quality cloud network is too coarse to fully capture topographic influences. Nevertheless, the broadscale consistency between patterns of cloud and rainfall variations indicates that the new total cloud amount dataset is able to adequately describe the broadscale patterns of change over Australia. Favourable simple comparisons between surface and satellite measures of cloudiness suggest that satellites may ultimately provide the means for monitoring long-term changes in cloud over Australia. However, due to the relative shortness and homogeneity problems of the satellite record, a robust network of surface cloud observations will be required for many years to come.