Integrating long term satellite data and in situ observations to study snow-albedo-temperature feedback over the Tibetan Plateau

The Tibetan Plateau (TP), also considered as the Third Pole, is extremely vulnerable to the anthropogenic climate change and has great impacts on local/regional climate, ecosystem, water resource and human society. Despite its importance, the understanding of how and why the TP's environment has changed still remains uncertain. One major reason is the lack of available observations, such as, near surface air temperature (SAT). Due to TP's complex terrain and high altitudes, most stations measuring SAT are located at relatively low altitude, thus leading to larger uncertainty when only station measurements were used. In this study, we present a high resolution (0.05°) gridded SAT dataset for TP from 2000-2016. This dataset is generated using the rule-based Cubist regression model, a robust machine learning model, to integrate MODIS satellite data (including land surface temperature and radiation products) with in situ measurements. This machine learning model enabled dataset provides daily average SAT estimation under all sky conditions. The dataset shows high accuracy (RMSE: 1.8~2.3 °C, Bias: -0.1~0.05 °C) when it is validated using station measurements. The MODIS based dataset shows a contrasting warming pattern between the east and west parts of the plateau. The western plateau, which is significantly undersampled by stations, shows higher warming rate comparing to the rest of the TP. To explain this contrasting warming pattern, we tested the hypothesis of snow-albedo-temperature feedback using satellite derived snow fraction and surface albedo products. We observed significant decrease of snow fractional coverage over the western plateau, which correlates to the notable reduction of surface albedo. Furthermore, the surface albedo show significant negative correlation with surface temperature with one month lag. This satellite based analysis suggests that the land-atmosphere interactions may further exacerbate the contrasting warming pattern over the plateau.