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ToolsLi, Zichen, Li, Qingxiang, Jiao, Boyang, Xu, Qiya, Wei, Sihao, Ru, Xutong, Si, Peng, Chao, Liya, Zhang, Hanyu, Lin, Jiaxue, Liao, Longshi, Zhang, Huixian, Huang, Boyin and Jones, Philip (2026) An Integrated Uncertainty Framework for the China-MST 3.0 Global Surface Temperature Data Set. Journal of Geophysical Research Atmospheres, 131 (8). ISSN 0148-0227
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Abstract
Global Mean Surface Temperature (GMST) is among the most important indicators of climate change, and its associated uncertainties affect the assessment of historical warming and the formulation of mitigation and adaptation policies. China-MST 3.0 is a newly updated global surface temperature data set that merges China-LSAT 2.1 for Land Surface Air Temperature (LSAT) and ERSST v6 for Sea Surface Temperature (SST). In this study, we develop a systematic and traceable uncertainty analysis framework for the construction process of this data set. Specifically, we comprehensively evaluate three components of LSAT uncertainty: observation, analysis, and coverage uncertainties, while describing SST uncertainty in terms of both parametric and reconstruction uncertainties. We also provide a quantitative assessment of the spatial and temporal evolution of these uncertainties. The results show that LSAT uncertainty is generally larger than that of SST and is mainly driven by coverage uncertainty. The overall uncertainty in GMST shows a significant downward trend, with the annual 1σ uncertainty falling below 0.03°C in recent decades, indicating high data reliability. However, uncertainty was high during the second-half of the 19th century and remains large at high latitudes in the Southern Hemisphere. Comparative analyses indicate that China-MST 3.0 is broadly consistent with other data sets in both the magnitude and temporal evolution of GMST uncertainty. These findings demonstrate the utility of China-MST 3.0 as a valuable tool for evaluating global warming since the 1850s.
| Item Type: | Article |
|---|---|
| Additional Information: | Data Availability Statement: Primary data supporting the findings of this study are publicly available on Zenodo at https://doi.org/10.5281/zenodo.18997705 (Li, 2026). These include the original data set (China‐MST3.0‐Imax, NetCDF format) used in this study and the processed uncertainty time‐series outputs (Excel format) presented in the manuscript. Due to the large data volume, the spatial distribution outputs of several uncertainty components cannot be fully archived in the repository. Additional data related to the spatial distributions of uncertainties are available from the corresponding author upon reasonable request. Model simulations used to estimate reconstruction uncertainty are obtained from the CMIP6 archive via the Earth System Grid Federation (https://esgf‐node.llnl.gov), specifically from the BCC‐CSM2‐MR developed by the Beijing Climate Center. The reanalysis data set used to estimate coverage uncertainty is the ERA5 reanalysis data set available from the Copernicus Climate Data Store (https://cds.climate.copernicus.eu/datasets/reanalysis‐era5‐single‐levels‐monthly‐means?tab=overview) |
| Uncontrolled Keywords: | sdg 13 - climate action ,/dk/atira/pure/sustainabledevelopmentgoals/climate_action |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
| UEA Research Groups: | Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Science > Research Groups > Climatic Research Unit |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 12 May 2026 16:10 |
| Last Modified: | 14 May 2026 15:15 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/102974 |
| DOI: | 10.1029/2025JD044732 |
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