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Surface mean temperature from the observational stations and multiple reanalyses over the Tibetan Plateau
Authors:Yan  Yuping  You  Qinglong  Wu  Fangying  Pepin  Nick  Kang  Shichang
Institution:1.National Climate Center, China Meteorological Administration, Beijing, 100081, China
;2.Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Science, Fudan University, Room 5002-1, Environmental Science Building, No. 2005 Songhu Road, Yangpu, Shanghai, 200438, China
;3.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China
;4.Department of Geography, University of Portsmouth, Portsmouth, PO1 2UP, UK
;5.State key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, 730000, China
;6.CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101, China
;
Abstract:

The Tibetan Plateau (TP), also called the “Third pole”, is sensitive to climate change due to extensive areas at high elevation presently dominated by snow and ice. In this study, observed surface temperature trends at 150 stations over the TP during 1979–2018 are analyzed and compared with surface temperatures from multiple reanalyses (NCEP1, NCEP2, ERA-Interim, MERRA, JRA55). Observed warming at the stations has a mean annual rate of 0.46 °C/decade during 1979–2018. Although all reanalyses underestimate observed temperatures (cold bias), most reproduce much of the inter-decadal variations of surface temperature shown in the observations. Absolute errors of mean surface temperature (reanalysis minus observation) are closely correlated with elevation errors, suggesting that parts of the cold bias can be interpreted by elevation errors of reanalysis. After elevation-temperature correction, about half of the cold bias is typically eliminated, more for both ERA-Interim and JRA55. Compared with the observations, corrected NCEP2 surface temperatures still have larger cold biases, and fail to capture the overall warming over the TP. Since the elevation-temperature correction fails to improve trend magnitudes even when a significant proportion of the bias has been removed, this suggests that a more sophisticated modeling of the lapse rate in each reanalysis is required to realistically model warming trends across complex topography.

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