Abstract
Many of the observed changes of the climate system since the 1950s are unprecedented, and there is a high level of confidence in the conclusion that greenhouse gases (GHGs) have caused a substantial part of the observed global warming. In the meantime, we need to consider model errors, which are usually accumulated in long-term integration as a result of imperfect physical and numerical representations, when attributing climate changes using model simulations. Here, we present a new method of piecewise integration (PWI) with simulation corrected by observation at each step, to identify model error-induced biases of global warming in the Community Earth System Model (CESM). To confirm the hypothesis of constant model bias under different external forcing, we turn the original CESM into a less low-cloud version and take its historical and GHGs-fixed simulations as our “observations”. In the PWI historical and GHGs-fixed runs of the original CESM from 1958 to 2005, we use the difference between “historical observation” and PWI historical run to correct both PWI runs at the end of each 1-day step. The results show that the PWI can effectively reduce model’s cumulative errors and present a GHGs-induced global warming trend of 0.688 ℃ (48 yr)−1, which is very close to the “observational” trend of 0.683 ℃ (48 yr)−1, confirming the hypothesis of constant model bias under different external forcing. The continuous runs, as usually done by the Coupled Model Intercomparison Project (CMIP) models, present a much higher GHGs-induced global warming trend of 0.887 ℃ (48 yr)−1, which means that the model overestimates the GHGs’ role in global warming trend by 32.3% compared to our “observations”. Global distribution of this model bias is also discussed. The PWI method provides a new way to correct model biases in analyzing relative contributions of anthropogenic and natural radiative forcings to global warming.
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Acknowledgements
We are very grateful to Prof. Chongjian Qiu for recommending the piecewise integration method and giving guidance to this paper. This work was funded by the National Natural Science Foundation of China (U21A6001), the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0103), Project supported by Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No. 311021009).
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Li, Y., Liu, F., Wang, X. et al. A piecewise integration approach for model error-induced biases of greenhouse gas contribution to global warming. Clim Dyn 58, 3175–3186 (2022). https://doi.org/10.1007/s00382-021-06089-w
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DOI: https://doi.org/10.1007/s00382-021-06089-w