Abstract

Meteorological Office (MO) equations are used to calculate daily degree days from daily minimum and maximum air temperatures. The resultant degree days are widely used in building energy analysis for monitoring, targeting, prediction and exception reporting and their accuracy is consequently important. Regression analysis has been performed on minimum, maximum and average daily air temperatures and daily degree days from over 100 weather stations over a 20-year time period. The results show how the MO equations consistently overestimate the degree days. This overestimation becomes progressively severe as the air temperature increases relative to the base temperature used in the degree day calculation. The use of optimised equations containing the maximum, minimum and average temperatures in a day most accurately calculates degree days and where the daily average is not available, using the daily minimum and maximum with different coefficients to those used in the MO equations leads to a significant improvement in the calculated degree days. Practical applications: Degree day data is vital in building energy management. Often hourly temperatures are not available and degree days have to be calculated from the MO equations using daily minimum and maximum temperatures. These equations are approximations developed from limited datasets and this paper describes better equations using minimum and maximum data and further improved equations when average daily data is also available. The reductions in errors in either degree days or energy use is important for reducing errors in data extracted from the resultant performance charts.

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