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Satellite-Estimated Winter Mean Minimum Temperature (TN) Analysis Over 2000-2013 for the Tibet Autonomous Region of China

Due to the harsh environment, observation networks over the Tibetan Plateau (TP) are very sparse, which makes satellite data valuable for spatially explicit analyses. This study focuses on satellite-based estimations of minimum temperature (Tn) for the Tibet Autonomous Region (TAR). First, seasonal variation in the relationship between nighttime land surface temperature (LSTnight) and Tn at meteorological stations was investigated and winter time was found to be the period when LSTnight has the strongest predictive power for Tn. Then, a thin-plate spline interpolation method incorporating LSTnight as a covariate was implemented to obtain 1 km winter Tn over the TAR. Finally, the trend in winter Tn over 2000–2013 and the impacts of snow cover and elevation on the trend were explored. The main findings are as follows. (1) The introduction of LSTnight can greatly increase Tn estimation accuracy. (2) Negative Tn trends were prevalent over western and northern TAR regions, and a decreasing trend was detected in the regional mean Tn (-0.18 °C/decade). (3) The southeastern TAR, which has lower elevations (<4000 m) and higher snow coverage than other areas, showed the most significant warming trend in Tn (0.84 °C/decade). Temperature in this area was close to the melting point, indicating that snow-albedo feedback can be easily triggered. (4) There was a stronger correlation between LSTnight and Tn and an enhanced cold bias in LSTnight over higher elevations or areas with larger snow coverage.