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A climatology of surface–air temperature difference over the Tibetan Plateau: Results from multi‐source reanalyses
Author(s) -
Wang Xuejia,
Chen Deliang,
Pang Guojin,
Ou Tinghai,
Yang Meixue,
Wang Meng
Publication year - 2020
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.6568
Subject(s) - climatology , environmental science , plateau (mathematics) , forcing (mathematics) , seasonality , surface air temperature , monsoon , atmospheric sciences , precipitation , meteorology , geography , geology , mathematical analysis , statistics , mathematics
The Tibetan Plateau (TP), known as earth's “Third Pole,” influences regional and even global weather and climate systems through its mechanical and thermal‐dynamical forcing. Near‐surface (2 m) air temperature ( T a ) and surface (skin) temperature ( T s ) are two crucial parameters of land–atmosphere interactions and climate change. Their difference (Δ T = T s − T a ) determines the heating source over the TP that drives the Asian summer monsoon. This study focuses on climatology, inter‐annual variability, and long‐term trend of Δ T over the TP in the last four decades (1979–2018), based on four latest reanalysis datasets including ERA‐Interim, ERA5, MERRA2, and JRA55, along with observational data. We show that Δ T ‐based different datasets display fairly different climatology in terms of seasonality, spatial distribution, and long‐term trend. Δ T exhibits a clear seasonality with negative value in winter and positive ones in summer despite different strengths and timings presented by the reanalyses. Along with global warming, all reanalyses except JRA55 exhibit obvious downwards trends of Δ T in a spatially non‐uniform way. The median Δ T among the four reanalyses features uniform decreases in all seasons, with the most distinct area on the northern TP, as well as the largest and least decreases in autumn and spring, respectively. Further analysis shows that the differences in Δ T are most likely associated with discrepancies in radiation forcing, snow cover, wind speed, and boundary layer height within the reanalyses. The present findings highlight the difficulty for the state‐of‐the‐art reanalyses to represent the climate change over the TP and point to possible factors behind the deficiencies identified.