On the impacts of computing daily temperatures as the average of the daily minimum and maximum temperatures

Abstract

Daily temperature values are generally computed as the average of the daily minimum and maximum observations, which can lead to biases in the estimation of daily averaged values. This study examines the impacts of these biases on the calculation of climatology and trends in temperature extremes at 409 sites in North America with at least 25 years of complete hourly records. Our results show that the calculation of daily temperature based on the average of minimum and maximum daily readings leads to an overestimation of the daily values of ~ 10+ % when focusing on extremes and values above (below) high (low) thresholds. Moreover, the effects of the data processing method on trend estimation are generally small, even though the use of the daily minimum and maximum readings reduces the power of trend detection (~ 5–10% fewer trends detected in comparison with the reference data).