Articles | Volume 14, issue 4
https://doi.org/10.5194/essd-14-1677-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-1677-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
11 Apr 2022
Data description paper |
| 11 Apr 2022
| 11 Apr 2022
Description of the China global Merged Surface Temperature version 2.0
Wenbin Sun
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China
current address: Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
Yang Yang
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China
current address: Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
Liya Chao
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China
current address: Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
Wenjie Dong
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China
current address: Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
Boyin Huang
National Centers of Environmental Information, NOAA, Asheville, North Carolina, USA
Phil Jones
Climate Research Unit, University of East Anglia, Norwich, UK
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
current address: Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
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- Newly reconstructed Arctic surface air temperatures for 1979–2021 with deep learning method Z. Ma et al. 10.1038/s41597-023-02059-5
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- Another scanning test of trend change in regression coefficients applied to monthly temperature on global land and sea surfaces J. Jiang 10.1007/s00704-023-04649-0
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12 citations as recorded by crossref.
- Recent cooling enhances glacier resilience to global warming in the northern Karakoram: Evidence from tree rings W. Liu et al. 10.1016/j.palaeo.2025.112836
- An intensification of surface Earth’s energy imbalance since the late 20th century X. Li et al. 10.1038/s43247-024-01802-z
- Newly reconstructed Arctic surface air temperatures for 1979–2021 with deep learning method Z. Ma et al. 10.1038/s41597-023-02059-5
- Dynamic modeling of topsoil organic carbon and its scenarios forecast in global Mollisols regions Y. Bao et al. 10.1016/j.jclepro.2023.138544
- Changes in Atmospheric Gaseous Elemental Mercury Concentrations and Isotopic Compositions at Mt. Changbai During 2015–2021 and Mt. Ailao During 2017–2021 in China X. Wu et al. 10.1029/2022JD037749
- The Detection and Attribution of Northern Hemisphere Land Surface Warming (1850–2018) in Terms of Human and Natural Factors: Challenges of Inadequate Data W. Soon et al. 10.3390/cli11090179
- Evaluation of the relationships and uncertainties of airborne and ground-based sea ice surface temperature measurements against remotely sensed temperature records P. Fan et al. 10.1080/17538947.2022.2143585
- Arctic warming trends and their uncertainties based on surface temperature reconstruction under different sea ice extent scenarios Z. Li et al. 10.1016/j.accre.2023.06.003
- Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature (CMST) Dataset Z. Li et al. 10.1007/s00376-023-3200-9
- Constraining the entire Earth system projections for more reliable climate change adaptation planning C. Li et al. 10.1126/sciadv.adr5346
- Another scanning test of trend change in regression coefficients applied to monthly temperature on global land and sea surfaces J. Jiang 10.1007/s00704-023-04649-0
- A new global land–ocean merged surface temperature dataset since the 1850s: the CMA-GMST dataset L. Chen et al. 10.1007/s00382-025-07614-x
Latest update: 29 May 2025
Short summary
The new China global Merged Surface Temperature CMST 2.0 is the updated version of CMST-Interim used in the IPCC's AR6. The updated dataset is described in this study, containing three versions: CMST2.0 – Nrec, CMST2.0 – Imax, and CMST2.0 – Imin. The reconstructed datasets significantly improve data coverage, especially in the high latitudes in the Northern Hemisphere, thus increasing the long-term trends at global, hemispheric, and regional scales since 1850.
The new China global Merged Surface Temperature CMST 2.0 is the updated version of CMST-Interim...
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