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An assessment of temperature simulations by CMIP6 climate models over the Tibetan Plateau and differences with CMIP5 climate models

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Abstract

Based on observational data from 1961 to 2014, the ability of 20 global climate models (GCMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate surface air temperature climatology and variability over the Tibetan Plateau (TP) is evaluated. The possible difference between the simulations of CMIP6 models and temperature simulations by models participating in the fifth phase of the CMIP (CMIP5) over the TP is also examined. The results reveal that most GCMs have the ability to reproduce climatological patterns and seasonal spatial variations in the surface air temperature. However, most GCMs have a cold bias, with a mean underestimation of 0.05–8.28 °C, and the multimodel ensemble means (MME) and medians of 20 GCMs underestimate the climatological mean over the TP by approximately 2.51 °C and 2.22 °C for 1961–2014. Regarding annual temperature, the top five GCMs with the least amount of bias for both the spatial distribution and regional-averaged temperature are NESM3, UKESM1.0-LL, CESM2, HadGEM3-GC3.1-LL, and GISS-ES.1-G. The cold bias of GCMs over the eastern TP is smaller than that over the TP, and the cold bias is more serious over the western TP. The MME and multimodel median values of 20 GCMs are − 2.00 °C and − 1.94 °C over the eastern TP, respectively, while they are − 3.00 °C and − 2.35 °C over the western TP. Regarding seasonal temperature, outputs from CMIP6 GCMs also reveal a significant cold bias over the western TP that is particularly prominent in spring and winter. Compared with CIMP5 simulations, the CIMP6 models seem to show very limited improvement over the TP. Cold bias is more serious for annual, spring, summer, and winter simulations in CMIP6 than in CMIP5, especially over the western TP. Nevertheless, the simulations of the geographical distribution of annual and seasonal temperatures are further improved in CMIP6. Moreover, over the northeastern TP, such as Tsaidam Basin and Qilian Mountain, GCMs from CMIP6 show slight improvement.

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Availability of data and material

All the data used in this work are public. The CMIP6 data are provided online at https://esgf-node.llnl.gov/projects/cmip6/; the CMIP5 data can obtain online at https://esgf-node.llnl.gov/search/cmip5/; observation data set CN05.1 are provided by the National Climate Centre of China (Wu and Gao 2013).

Code availability

NCAR Command Language (NCL) is used to process the data analysis and plot the figures.

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Acknowledgements

We acknowledge the organizations that provided the model simulations and observation data for our study (listed in Tables 1 and 2).

Funding

This work was jointly supported by The Second Tibetan Plateau Scientific Expedition and Research (STEP) program (2019QZKK010203), the National Natural Science Foundation of China (41775072 and 42075019), the National Key Research and Development Program of China (2018YFC1505702), the Science and Technology Program of Sichuan province (2020JDJQ0050 and 2019JDJQ0001), and the Scientific Research Foundation of Chengdu University of Information Technology (KYTZ201812).

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Authors and Affiliations

  1. School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, Sichuan Province, China

    Qin Hu, Wei Hua, Kaiqing Yang, Jing Ming, Pan Ma, Yong Zhao & Guangzhou Fan

  2. Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu, 610225, Sichuan Province, China

    Qin Hu, Wei Hua & Guangzhou Fan

  3. Meteorological Disaster Prediction and Warning Engineering Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, 610225, Sichuan Province, China

    Wei Hua & Guangzhou Fan

Authors
  1. Qin Hu
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  2. Wei Hua
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  3. Kaiqing Yang
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  4. Jing Ming
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  5. Pan Ma
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  6. Yong Zhao
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  7. Guangzhou Fan
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Contributions

Qin Hu contributed to data analysis, major figure plotting, and manuscript drafting; Wei Hua contributed to conceptualization, design, and writing; Kaiqing Yang, Jing Ming, and Pan Ma contributed to data collection, calculation, data analysis, and figure plotting; Yong Zhao and Guangzhou Fan contributed in data curation, validation, and manuscript revision.

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Correspondence to Wei Hua.

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Hu, Q., Hua, W., Yang, K. et al. An assessment of temperature simulations by CMIP6 climate models over the Tibetan Plateau and differences with CMIP5 climate models. Theor Appl Climatol 148, 223–236 (2022). https://doi.org/10.1007/s00704-022-03944-6

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