A Comparison of Two Daily Temperature Averaging Methodologies: Uncertainties and Spatial Variability

Traditionally, daily average temperature is computed by taking the mean of two values- the maximum temperature over a 24-hour period and the minimum temperature over the same period. These data form the basis for numerous studies of long-term climatologies (e.g. 30-year normals) and recent temperature trends and changes. However, many first-order weather stations (e.g. airports) also record hourly temperature data. Using an average of the 24 hourly temperature readings to compute daily average temperature should provide a more precise and representative estimate of a given day's temperature. These two methods of daily temperature averaging (max+min/2, average of 24 hourly temperature values) were computed and mapped for all first-order weather stations across the United States for the 30-year period 1981-2010. Preliminary data analysis indicates a statistically significant difference between the two methods, as well as an overestimation of temperature by the traditional method (Tmax + Tmin /2), particularly in southern and coastal portions of the Continental U.S. The likely explanation for the long-term difference between the two methods is the underlying assumption of the twice-daily method that the diurnal cycle of temperature follows a symmetrical pattern. There is an apparent relationship of these differences to factors such as land use/land cover, snow cover duration, and the regional synoptic climatology, which help explain the spatial variability. Additional analysis of station normals based on hourly data should have numerous applications and benefits to society, such as better determination of heat wave severity and energy usage needs.