Land surface skin temperatures from a combined analysis of microwave and infrared satellite observations for an all-weather evaluation of the differences between air and skin temperatures

[1] A neural network inversion scheme including first guess information has been developed to retrieve surface temperature T-s, along with atmospheric water vapor, cloud liquid water, and surface emissivities over land from a combined analysis of Special Sensor Microwave/Imager (SSM/I) and International Satellite Cloud Climatology Project (ISCCP) data. In the absence of routine in situ surface skin measurements, retrieved T-s values are evaluated by comparison to the surface air temperature T-air measured by the meteorological station network. The T-s - T-air difference shows all the expected variations with solar flux, soil characteristics, and cloudiness. During daytime the T-s - T-air difference is driven by the solar insulation, with positive differences that increase with increasing solar flux. With decreasing soil and vegetation moisture the evaporation rate decreases, increasing the sensible heat flux, thus requiring larger T-s - T-air differences. Nighttime T-s - T-air differences are governed by the longwave radiation balance, with T-s usually closer or lower than T-air. The presence of clouds dampens all the difference. After suppression of the variability associated to the diurnal solar flux variations, the T-s and T-air data sets show very good agreement in their synoptic variations, even for cloudy cases, with no bias and a global rms difference of similar to2.9 K. This value is an upper limit of the retrieval rms because it includes errors in the in situ data as well as errors related to imperfect time and space collocations between the satellite and in situ measurements.