Extrapolation of daily air temperatures of Egypt from MODIS LST data

The limited and poor spatial distribution of meteorological stations is inadequate to reconstruct accurate regional air temperature maps, which are important for environmental planning and resources management. This study aimed to generate a gridded dataset of max/min daily surface air temperatures for Egypt based on remotely sensed data acquired from the MODIS land surface temperature (LST) product. Linear regression analysis was performed between observed air temperatures from ground weather stations and LST records from satellite images. Regression coefficients were as high as 0.8 between min air temperature and night LST data, compared to 0.77 for max air temperature and day LST. Statistical analysis reveals significant correlations (p < .01) for both regression relationships. MODIS data showed a satisfactory performance in producing regional monthly and annual as well as diurnal surface air temperatures maps for Egypt. MODIS data could also highlight the influence of topography, vegetation and lithology on air temperatures.

Automated summary

This study successfully generated a gridded dataset of daily surface air temperatures for Egypt using remotely sensed data, addressing the issue of limited meteorological station coverage. The dataset was able to highlight the influence of topography, vegetation, and lithology on air temperatures.