Evaluation of MODIS LST products over the Tibetan Plateau and plain areas with in situ measurements

Land surface temperature (LST) is a crucial physical parameter for hydrological, meteorological, climatological, and climate changestudies. To encourage the use of satellite-derived LST products in a wide range of applications, providingfeedback on product performance over regional and global scales is anurgenttask. However, consideringthat the uncertainty of newly released LST products isstill unclear, it is urgently necessary to performa comprehensive validation and error analysis, especially in areas with special geographical and weather conditionssuch as the Tibetan Plateau (TP). In particular, fewer studies have been concerned with the degraded LST retrieval accuracy over the TP because ofthe sparse ground measurements. In this study, MODIS LST products (C6) were comprehensively evaluated based on independent ground observation systems with different atmospheric and LSTconditions. The in situ measurements collected from the TORP and SURFRAD systems are located on the North American Plain andtheTP, respectively, incorporating various land cover types, including barrenland, grassland, cropland, shrublandand sparse and dense vegetation, among others.Prior to the validation, LST products with different spatial resolutions were compared to ensure the spatial representativeness of ground-based measurements at satellite pixel scale. The evaluation results indicated that relatively high-quality in situ LST can be obtained during nighttime with relatively homogeneous spatial distribution. Compared with the North American Plain(with a mean RMSE of 1.56 K), MODIS LST retrieval has largerdiscrepancies (mean RMSE of 2.34K) over the TP withcomplex terrain and variable weather. Various factorsaffecting LST retrieval accuracy were analyzed, which were categorized into1) the simulated atmospheric and surface temperature condition settings, 2) the input data uncertainty, and 3)others. Among them, the emissivity determination is the primary source of the uncertainty in the generalized split-window algorithm, where the overestimated emissivity causes an underestimation of LST. It is expected to developnew LST retrieval algorithm to meet the quality specifications of usersover the TP. Overall, this study identifies critical further research needs and improve the understanding of LST product performance under complex circumstance.