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Abstract

Daily mean, maximum and minimum surface air temperature data were gathered from a network of automatic weather stations (AWS) within the Moor House National Nature Reserve in northern England. Five AWS were installed next to the official Environmental Change Network weather station at Moor House. Data were compared graphically and correction constants were calculated to adjust data from each AWS to the standard of the official station by optimising the concordance correlation coefficient. Each corrected station was re-located next to one of five in-situ stations in and around the reserve, allowing correction of all temperature sensors to a common standard. The mean error associated with measured daily mean, maximum and minimum temperature for each sensor does not exceed +/- 0.2 K. The procedure quantifies a source of systematic measurement error, improving the identification of spatial temperature differences between stations.

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Investigating sensing properties of poly-(dioctylfluorene) based planar sensor

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