2014
DOI: 10.1007/s13351-014-3027-5
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Validation and application of reanalysis temperature data over the Tibetan Plateau

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Cited by 30 publications
(33 citation statements)
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“…Associated with the TP warming, the snow depth is found to significantly decrease in southeastern TP (Figure f), which could amplify the warming there [ Y. Xu et al , ]. The observed warming in recent decades is also the most significant in the marginal areas of TP [ Zou et al , ]. Our simulations suggest an alternative contributor, i.e., the anthropogenic BC, to the observed warming over TP, besides the global warming.…”
Section: Resultsmentioning
confidence: 99%
“…Associated with the TP warming, the snow depth is found to significantly decrease in southeastern TP (Figure f), which could amplify the warming there [ Y. Xu et al , ]. The observed warming in recent decades is also the most significant in the marginal areas of TP [ Zou et al , ]. Our simulations suggest an alternative contributor, i.e., the anthropogenic BC, to the observed warming over TP, besides the global warming.…”
Section: Resultsmentioning
confidence: 99%
“…Recent studies [e.g., Wang and Zeng , ; Bao and Zhang , ; Zou et al ., ] have found that global reanalysis products contain large errors in surface meteorological variables and are not suitable for surface processes modeling for the TP. In this study, a long‐term (1979–2014) forcing data set developed by the hydrometeorological research group at the Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS) was used to drive the Flake model.…”
Section: Study Area and Datamentioning
confidence: 99%
“…With respect to CRU, similar bias distributions are observed, but numerical values are generally about 1°C higher. The cold bias on the Tibetan plateau (with its very complex terrain and high altitude) is partially inherited from the driving data ERA‐Interim which, although providing a realistic representation of the topographic effects and consistent with the topography of the plateau, show a cold bias (0.6°C) compared to observed temperatures at 13 radiosonde stations [ Zou et al, ]. Moreover, cold bias at high altitude is a typical model deficiency of COSMO‐CLM and is due to underestimation of the model orography, and might also be due to the insufficient ability of the model to reproduce the temperature inversions recorded in winter [ Du et al, ].…”
Section: Validation Of Cosmo‐clm Over 1980–2011mentioning
confidence: 99%