Surface temperature and water vapour retrieval from MODIS data

This paper gives operational algorithms for retrieving sea (SST), land surface temperature (LST) and total atmospheric water vapour content (W) using Moderate Resolution Imaging Spectroradiometer (MODIS) data. To this end, the MODTRAN 3.5 radiative transfer program was used to predict radiances for MODIS channels 31, 32, 2, 17, 18 and 19. To analyse atmospheric effects, a simulation with a set of radiosonde observations was used to cover the variability of surface temperature and water vapour concentration on a worldwide scale. These simulated data were split into two sets (DB1 and DB2), the first one (DB1) was used to fit the coefficients of the algorithms, while the second one (DB2) was used to test the fitted coefficients. The results show that the algorithms are capable of producing SST and LST with a standard deviation of 0.3 K and 0.7 K if the satellite data are error free. The LST product has been validated with in situ data from a field campaign carried out in the Mississippi (USA), the results show for the LST algorithm proposed a root mean square error lower than 0.5K. Regarding water vapour content, a ratio technique is proposed, which is capable of estimating W from the absorbing channels at 0.905, 0.936, and 0.94,µm, and the atmospheric window channel at 0.865,µm, with a standard deviation (in the comparison with radiosonde observations) of 0.4 g cm−2.