Estimating average daytime and daily temperature profiles within Europe

Abstract

We present a methodology for estimating the average profiles of daytime and daily ambient temperature from a spatially-continuous database for any location within Europe. The primary database with 1-km grid resolution was developed by interpolation of monthly averages of 7 daily values of temperature: minimum and maximum and 5 measurements at 3-h intervals from 6:00 to 18:00 hours Greenwich Mean Time. With a little over 800 meteorological stations available, we obtained a cross-validation root mean square error of 1.0–1.2 °C, while the interpolation error is lower, at 0.5–0.7 °C. A polynomial fit was applied to estimate the daytime temperature profile (assuming only time from sunrise to sunset) from the interpolated 3-h measurements for each month. The curve fit coefficients make it possible to calculate a number of derived data, such as average daytime temperature, maximum daytime temperature and time of its occurrence within the region. An example demonstrates the coupling of the simulated daytime temperature profile with a model for assessing the relative efficiency of electricity generation by crystalline silicon photovoltaic modules. As an alternative to the polynomial fitting, a double-cosine method was applied to enable calculation of daily (24-h) temperature profiles for each month using interpolated minimum and maximum temperatures. Compared to the polynomial curve-fitting, this method does not offer lower errors, but it provides data which are more suitable for estimation of solar thermal heating or calculation of degree days for building heating/cooling.