Open Access
Open access
Journal of Southern Hemisphere Earth Systems Science, volume 75, issue 1

Comparison of temperature and humidity measurements from two separate weather stations at Camden Airport, Australia

Publication typeJournal Article
Publication date2025-01-16
scimago Q1
SJR1.849
CiteScore8.1
Impact factor2.5
ISSN22065865
Abstract

In Australia, meteorological measurements from air quality monitoring networks are an overlooked source of data for urban climatology and meteorology research and operations. The reasons for this are not clear but may include uncertainty in the quality of the observations. Here I compare over 1 million 1-min near surface air temperature (n = 516,334) and relative humidity (n = 516,717) measurements from two distinct observational stations at Camden Airport in New South Wales (NSW), Australia – the Bureau of Meteorology automatic weather station (AWS) and the NSW Department of Climate Change, Energy, the Environment and Water’s air quality monitoring station (AQMS). Annual mean bias in the AQMS temperature measurements was −0.14°C. There were seasonal and diurnal variations in temperature bias, with monthly mean bias varying from −0.27 to +0.06°C and mean hourly bias varying between −0.39 and +0.11°C. Annual mean bias in AQMS humidity measurements was −0.37%, monthly mean bias varied from −2.21 to +1.44% and bias in mean hourly measurements varied between −2.64 and +2.66%. Temperature and humidity mean biases were both within the range of the combined instrument uncertainties. The seasonal and diurnal signal in the bias is likely due to differences in instrument siting and the different radiation shields (Stevenson and multi-plate). This analysis suggests that temperature and humidity measurements from the NSW AQMS are of high quality. The performance of the AQMS measurements matches the AWS measurements and, for most circumstances, the temperature and humidity measurements are comparable. Urban climatologists and meteorologists should consider data from air quality networks in their research and can use this data with confidence.

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