Abstract
ABSTRACTThe Tibetan Plateau (TP), acting as a large elevated land surface and atmospheric heat source during spring and summer, has a substantial impact on regional and global weather and climate. To explore the multi-scale temporal variation in the thermal forcing effect of the TP, here we calculated the surface sensible heat and latent heat release based on 6-h routine observations at 80 (32) meteorological stations during the period 1979–2016 (1960–2016). Meanwhile, in situ air-column net radiation cooling during the period 1984–2015 was derived from satellite data. This new dataset provides continuous, robust, and the longest observational atmospheric heat source/sink data over the third pole, which will be helpful to better understand the spatial-temporal structure and multi-scale variation in TP diabatic heating and its influence on the earth’s climatic system.
Highlights
The Tibetan Plateau (TP) plays a key role in the formation and variation in the Asia summer monsoon via its mechanical and thermal effects (An et al, 2015; Boos & Kuang, 2010; Luo & Yanai, 1984; Wu et al, 2015; Ye & Gao, 1979; Yeh, 1950; Zhao & Chen, 2001)
The atmospheric heat source/sink dataset over the TP in this study consists of three variables: surface sensible heat flux SH, latent heat release LH and net radiation flux RC
According to the estimating method proposed by Yang, Qin, Guo, Zhou, and Ma (2009), air temperature at 1.5 m and surface temperature and wind speed at 10 m in China Meteorological Administration (CMA) station observations are used to calculate surface sensible heat flux, while the latent heat release is estimated using CMA precipitation data
Summary
The Tibetan Plateau (TP) plays a key role in the formation and variation in the Asia summer monsoon via its mechanical and thermal effects (An et al, 2015; Boos & Kuang, 2010; Luo & Yanai, 1984; Wu et al, 2015; Ye & Gao, 1979; Yeh, 1950; Zhao & Chen, 2001). Because of the complexity of the land surface process over the TP, most reanalysis data fail to provide an accurate measure of its statistical features let alone its multi-timescale variability. This makes station observations over the TP important to estimate its thermal conditions. Compared with the study of Duan and Wu (2008), a longer and continuous dataset with more advanced parameterization scheme is required to support for research on the TP heating effect and a reliable reference for the evaluation of the quality of different reanalysis datasets
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