Observation-Time-Dependent Biases and Departures for Daily Minimum and Maximum Air Temperatures

Abstract

Non-calendar-day observations of 24-h minimum and maximum air temperatures can be considerably different from calendar-day or midnight observations. This paper examines the influence of time-of-observation on 24-h temperature observations. Diurnal minimum and maximum temperatures measured at common observation times (0700 and 1700 LST) are compared with minimum and maximum temperatures measured at midnight. The principal methods make use of hourly temperature observations, sampled over 24-h moving windows, to approximate once-daily observations. Surprisingly, non-calendar-day observations are similar to calendar-day observations on a majority of days. When differences do occur, however, they can be large and of either sign. Differences between 1700 LST observations and midnight observations are typically smaller than those arising from 0700 LST observations. Daily differences can be grouped by temperature extrema recorded on the incorrect day (a bookkeeping problem) or temperature extrema recorded on two successive days (bias). Bias scenarios arise when very cold mornings or very warm afternoons influence the temperature measured on successive days. Locations or seasons with the least day-to-day temperature variability often display the least time-of-daily-observation influence on temperature. Determining those days on which large departures and biases are likely to occur is possible by measuring day-to-day temperature persistence. First-order differences of daily time series may be used explicitly in adjustment procedures for morning observations of maximum temperature. Otherwise, first-order differences may be used to determine those days on which large observation-time differences are likely or those days on which observation-time dependencies are trivial.