Search

An empirical methodology in modelling and mapping air temperatures (monthly minimum, mean and maximum), monthly relative humidities and cumulative precipitation using geographical information system (GIS) techniques was proposed. Linear regression analyses were developed between weather data and some of the geographical and climatical variables (altitude, monthly mean temperature and relative humidity) of the study area. Data were obtained from 11 different meteorological stations located in the study area, and elaborated from a 250 m resolution digital elevation model (DEM). Analyses of digital layers of each independent variable with basic GIS techniques were used, and the most suitable models obtained from regression analysis were used to create final maps. The coefficients of determination for monthly mean and minimum temperatures were 0.68 and 0.98, respectively. In the case of monthly relative humidity, r2 ranged between 0.80 and 0.98, while in the case of monthly cumulative precipitation, it ranged from 0.82 to 0.98, respectively. Maximum monthly temperature, particularly for the summer months had a low relationship with elevation, therefore determination coefficient ranged from 0.46 to 0.81. When spatial information is available, the proposed method could be used as an alternative to classical interpolation techniques. Copyright © 2007 Royal Meteorological Society [ABSTRACT FROM AUTHOR]