2019
DOI: 10.1029/2018jd030069
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Distribution and Variation of the Surface Sensible Heat Flux Over the Central and Eastern Tibetan Plateau: Comparison of Station Observations and Multireanalysis Products

Abstract: Surface sensible heat fluxes (SH) over Tibetan Plateau (TP) dictate the seasonal conversion, onset and maintenance of the Asian monsoon. Spatiotemproal variability in SH over central and eastern TP (CETP) from reanalysis products (i.e., JRA55, ERA‐Interim, NCEP1, and NCEP2) and derived using bulk transfer approximations applied to observations is characterized for all seasons during 1980–2015 and is diagnosed in the context of two important drivers of variability: wind speed and land‐air temperature difference… Show more

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Cited by 29 publications
(17 citation statements)
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“…As a result of limited observations and the nonuniform distribution of routine meteorological monitoring stations over the Tibetan Plateau, it is still challenging to accurately estimate diabatic heating in this region, although the TPSH in this work is generally consistent with that calculated by Chen, Pryor, et al (2019) in terms of intensity and variation.…”
Section: Discussionsupporting
confidence: 76%
“…As a result of limited observations and the nonuniform distribution of routine meteorological monitoring stations over the Tibetan Plateau, it is still challenging to accurately estimate diabatic heating in this region, although the TPSH in this work is generally consistent with that calculated by Chen, Pryor, et al (2019) in terms of intensity and variation.…”
Section: Discussionsupporting
confidence: 76%
“…Surface SH over the TP is the dominant source of diabatic heating and reaches its maximum during the boreal spring (Yeh and Gao 1979;Liu et al 2015;Duan et al 2017;Zhao et al 2018;Chen et al 2019). The positive surface SH anomaly over the TP generates negative vorticity anomaly at higher levels, which influences the atmospheric circulation across the northern hemisphere by triggering Rossby wave trains (Wu et al 1996(Wu et al , 2015Liu et al 2017).…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, Δ T time series of the reanalyses exhibit large fluctuations in DJF and MAM, indicating large year‐to‐year variability. Similar decreasing trends are also reported by NCEP reanalysis data (Chen et al ., 2019). Taken together, the median Δ T has decreased significantly in four seasons from 1979 to 2018 (Table S2), in accord with the decline of SHF (Wang et al ., 2013; Duan et al ., 2018) and the reduction of heating ability in recent decades (Yang et al ., 2011).…”
Section: Climatology Of δT From Multi‐source Reanalysesmentioning
confidence: 99%
“…For instance, MERRA has a high correlation with observations of surface meteorological variables (Wang and Zeng, 2012). ERA‐Interim data shows relatively small cold bias in T a (Wang et al ., 2017) and better performance in water cycle (Wang and Zeng, 2012), as well as SHF on the TP (Chen et al ., 2019).…”
Section: Introductionmentioning
confidence: 99%