This study proposes an empirical methodology for modelling and mapping the air temperature (mean maximum, mean and mean minimum) and total precipitation, all of which are monthly and annual, using geographical information systems (GIS) techniques. The method can be seen as an alternative to classical interpolation techniques when spatial information is available. The geographical area used to develop and apply this model is Catalonia (32 000 km2, northeast Spain). We have developed a multiple regression analysis between these meteorological variables as the dependent ones, and some geographical variables (altitude (ALT), latitude (LAT), continentality (CON), solar radiation (RAD) and a cloudiness factor (CLO)) as the independent ones. Data for the dependent variables were obtained from meteorological stations, and data for the independent variables were elaborated from a 180 m resolution digital elevation model (DEM). Multiple regression coefficients (bn) were used to build final maps, using digital layers for each independent variable, and applying basic GIS techniques. The results are very satisfactory in the case of mean air temperature and mean minimum air temperature, with coefficients of determination (R2) between 0.79 and 0.97, depending on the month; in the case of mean maximum air temperature, R2 ranges between 0.70 and 0.89, while in the case of precipitation, it ranges between 0.60 and 0.91. Copyright © 2000 Royal Meteorological Society
International Journal of Climatology – Wiley
Published: Nov 30, 2000
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