Monitoring air and Land Surface Temperatures from remotely sensed data for climate-human health applications

This study proposes a methodology to infer maximum air temperature from space using observations from polar orbiting satellite MODIS. A previous study showed that minimum Land Surface Temperature (LST) derived from MODIS night-time images provides a good surrogate for minimum air temperature while the retrieval of maximum air temperature is less straightforward. The objective of this work is to estimate maximum air temperatures through the extrapolation of the minimum temperature derived from MODIS according to the diurnal cycle. The diurnal cycle parameters (i.e. phase and amplitude) which are used to estimate the maximum air temperature are determined locally using data from the WORDCLIM database. The proposed approach is applied over four different areas in Africa (Eritrea, Ethiopia, Botswana and Madagascar) based on measurements collected in 28 different stations over the period 2002-2008. An acceptable agreement between maximum air temperature estimated and observed temperatures was noticed. This implies that satellite imagery has an interesting potential in inferring maximum air temperature at an interesting temporal and spatial resolution.