Influence Study of Adjacency Effect Caused by Dust Aerosols on Thermal Infrared LST Retrieval

Land surface temperature (LST) is a critical parameter for many applications. A default aerosol type and a fixed aerosol loading were commonly used in the development of LST retrieval algorithms. However, numerical simulations showed that a significant bias up to -3 K was found at nadir view if dust aerosol was not considered in the LST retrieval algorithm. To reduce the influence of dust aerosol on LST estimation, a three-channel algorithm was proposed based on a widely used two channel algorithm for clear-sky conditions. With simulated data of MODIS channels 29, 31, and 32, the LST could be estimated with a root mean squire error (RMSE) of 1.4 K when viewing zenith angle (VZA) was 0° and aerosol optical depth (AOD, at 0.55 μm) less than 1.0; the maximum RMSE was 2.3 K and 2.2 K for the day-time and night-time algorithm, respectively, when VZA less than 60°. In case of clear-sky conditions, namely AOD=0, the RMSE was less than 1.2 K and 1.8 K when VZA=0° and 60°, respectively. It indicates that the proposed three-channel algorithm can be used to estimate LST not only for dust aerosol skies but also for clear-sky conditions. In addition, the influences of adjency effect induced by the scatter of dust aerosol are also studied, it shows that with considering the adjency affect the RMSE of LST retrieval algorithm increased about 0.5 K.