Abstract
Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated global land surface air temperature and a land and marine surface temperature dataset, referred to as China global land surface air temperature (C-LSAT) and China merged surface temperature (CMST), to estimate trends in the global mean ST (combining land surface air temperature and sea surface temperature anomalies) with the data uncertainties being taken into account. Comparing with existing datasets, the statistical significance of the global mean ST warming trend during the past century (1900–2017) remains unchanged, while the recent warming trend during the “hiatus” period (1998–012) increases obviously, which is statistically significant at 95% level when fitting uncertainty is considered as in previous studies (including IPCC AR5) and is significant at 90% level when both fitting and data uncertainties are considered. Our analysis shows that the global mean ST warming trends in this short period become closer among the newly developed global observational data (CMST), remotely sensed/Buoy network infilled datasets, and reanalysis data. Based on the new datasets, the warming trends of global mean land SAT as derived from C-LSAT 2.0 for the period of 1979–2019, 1951–2019, 1900–2019 and 1850–2019 were estimated to be 0.296, 0.219, 0.119 and 0.081 °C/decade, respectively. The warming trends of global mean ST as derived from CMST for the periods of 1998–2019, 1979–2019, 1951–2019 and 1900–2019 were estimated to be 0.195, 0.173, 0.145 and 0.091 °C/decade, respectively.
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Acknowledgements
This study is supported by the Natural Science Foundation of China (Grant: 41975105), the National Key R&D Program of China (Grant: 2018YFC1507705; 2017YFC1502301). And thanks Dr. Geert van Oldenborgh from Royal Netherlands Meteorological Institute (KNMI) for providing several global SAT/ST datasets on Climate Explorer website (http://climexp.knmi.nl/) for calculating the temperature change trends in this paper.
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Li, Q., Sun, W., Yun, X. et al. An updated evaluation of the global mean land surface air temperature and surface temperature trends based on CLSAT and CMST. Clim Dyn 56, 635–650 (2021). https://doi.org/10.1007/s00382-020-05502-0
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DOI: https://doi.org/10.1007/s00382-020-05502-0