MAPPING REGIONAL AIR-TEMPERATURE FIELDS USING SATELLITE-DERIVED SURFACE SKIN TEMPERATURES

Screen air temperature is an important climatological variable and acc urate mapping of its spatial and temporal distribution is of great int erest for various scientific disciplines. The low spatial density of m eteorological stations, however, results in relatively large errors du ring data interpolation and makes it difficult to retrieve the spatial pattern of the temperature field Errors of the order of 1 to 3 K are mentioned in the literature. The current study investigates the possib ilities of mapping and monitoring the spatial distribution of daily ma ximum air temperatures with the help of time series of NOAA-AVHRR imag es. The study has been performed for the Mediterranean region of Andal usia in southern Spain Data analysis included 31 meteorological statio ns and 148 AVHRR images from the year 1992. Regression analysis betwee n the daily maximum air temperature (T-max) and the mean surface skin temperature (T-s) retrieved for 11 km(2) image windows centred over ea ch station, suggests that T-max is strongly linked to T-s in the given environment (mean R-2 = 0.823) and that for individual stations T-max can be retrieved from T-s with a mean error of about 2 K. The spatial representativity of the station measurements as well as the influence of altitude and land use on the results are discussed Finally, the po ssibilities of retrieving the spatial pattern of T-max have been evalu ated through a cross-validation approach. In this analysis T-max has b een predicted for each station and for all days of available image dat a based on a regression model retrieved from all other stations. Again the results indicate that we are able to reproduce the daily distribu tion of maximum air temperatures with a mean error of the order of 2 t o 2.5 K, using satellite-retrieved surface skin temperatures. In addit ion, the method allows for the detection of stations with a low spatia l representativity or a pronounced measurement bias. Future research w ill aim at the inclusion of further physiographic data, the grouping o f stations according to site-specific characteristics and an analysis according to seasons. (C) 1997 Royal Meteorological Society.