Standardisation of temperature observed by automatic weather stations

Daily mean, maximum and minimum surface air temperature data were gathered from a network of automatic weather stations (AWS) within the Moor House Na tional Nature Reserve in northern England. Five AWS were installed next to the official Environmental Change Network weather station at Moor House. Da ta were compared graphically and correction constants were calculated to ad just data from each AWS to the standard of the official station by optimisi ng the concordance correlation coefficient. Each corrected station was re-l ocated next to one of five in-situ stations in and around the reserve, allo wing correction of all temperature sensors to a common standard. The mean e rror associated with measured daily mean, maximum and minimum temperature f or each sensor does not exceed +/-0.2 K. The procedure quantifies a source of systematic measurement error, improving the identification of spatial te mperature differences between stations.