Using Land Cover, Population, and Night Light Data for Assessing Local Temperature Differences in Mainz, Germany

Abstract

rban areas are believed to affect temperature readings, thereby biasing the estimation of twentieth-century warming at regional to global scales. The precise effect of changes in the surroundings of meteorological stations, particularly gradual changes due to urban growth, is difficult to determine. In this paper, data from 10 temperature stations within 15 km of the city of Mainz (Germany) over a period of 842 days are examined to assess the connection between temperature and the properties of the station surroundings, considering (i) built/paved area surface coverage, (ii) population, and (iii) night light intensity. These properties were examined in circles with increasing radii from the stations to identify the most influential source areas. Daily maximum temperatures Tmax, as well as daily average temperatures, are shown to be significantly influenced by elevation and were adjusted before the analysis of anthropogenic surroundings, whereas daily minimum temperatures Tmin were not. Significant correlations (p < 0.1) between temperature and all examined properties of station surroundings up to 1000 m are found, but the effects are diminished at larger distance. Other factors, such as slope and topographic position (e.g., hollows), were important, especially to Tmin. Therefore, properties of station surroundings up to 1000 m from the stations are most suitable for the assessment of potential urban influence on Tmax and Tmin in the temperate zone of central Europe.