Based on C-LSAT2.0, using high- and low-frequency components reconstruction methods, combined with observation constraint masking, a reconstructed C-LSAT2.0 with 756 ensemble members from the 1850s to 2018 has been developed. These ensemble versions have been merged with the ERSSTv5 ensemble dataset, and an upgraded version of the CMST-Interim dataset with 5° × 5° resolution has been developed. The CMST-Interim dataset has significantly improved the coverage rate of global surface temperature data. After reconstruction, the data coverage before 1950 increased from 78%–81% of the original CMST to 81%–89%. The total coverage after 1955 reached about 93%, including more than 98% in the Northern Hemisphere and 81%–89% in the Southern Hemisphere. Through the reconstruction ensemble experiments with different parameters, a good basis is provided for more systematic uncertainty assessment of C-LSAT2.0 and CMST-Interim. In comparison with the original CMST, the global mean surface temperatures are estimated to be cooler in the second half of 19th century and warmer during the 21st century, which shows that the global warming trend is further amplified. The global warming trends are updated from 0.085 ± 0.004°C (10 yr)−1 and 0.128 ± 0.006°C (10 yr)−1 to 0.089 ± 0.004°C (10 yr)−1 and 0.137 ± 0.007°C (10 yr)−1, respectively, since the start and the second half of 20th century.
基于C-LSAT2.0陆表温度数据集, 本文作者采用高、低频分量重建的方法, 结合观测约束裁剪, 发展了1850–2018年集合 (756个成员) 重建C-LSAT2.0数据集. 在此基础上, 作者将C-LSAT2.0与ERSSTv5集合数据集融合, 发展了分辨率为5°×5°的全球表面温度数据集CMST-Interim. 该数据集的全球覆盖率较原GMST有明显的提升:在1950年以前由原来CMST的78%–81%增加到81%–99%之间, 1955年以后达到93%左右, 其中北半球超过了98%, 南半球在81%–89%之间. 不同参数的重建集合试验为C-LSAT2.0及CMST-Interim的不确定性评估提供了很好的基础. 与原CMST相比, CMST-Interim的全球平均温度距平在19世纪下半叶稍降低, 在21世纪则略升高, 从而证实了全球变暖进一步扩大的趋势: 1900–2018年和1950–2018年的全球变暖趋势明显增加, 从基于原CMST的 0.085 ± 0.004℃ (10 yr) −1 和 0.128 ± 0.006℃ (10 yr) −分别增加到了基于CMST-Interim的 0.089 ± 0.004°C (10 yr) −1 和 0.137 ± 0.007°C (10 yr) −1.
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This study is supported by the Natural Science Foundation of China (Grant: 41975105) and the National Key R&D Program of China (Grant: 2018YFC1507705; 2017YFC1502301).
The reconstructed C-LSAT2.0 and the upgraded version CMST-Interim datasets are available from http://atmos.sysu.edu.cn/ResearchDownload.
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Sun, W., Li, Q., Huang, B. et al. The Assessment of Global Surface Temperature Change from 1850s: The C-LSAT2.0 Ensemble and the CMST-Interim Datasets. Adv. Atmos. Sci. 38, 875–888 (2021). https://doi.org/10.1007/s00376-021-1012-3
- C-LSAT2.0 ensemble datasets
- high- and low-frequency components