Abstract
We provide a statistical review of the “optimal fingerprinting" approach presented in Allen and Tett (Clim Dyn 15:419-434, 1999) in light of the severe criticism of McKitrick (Checking for model consistency in optimal fingerprinting: a comment. Clim Dyn 58:405–411, 2022). Our review finds that the “optimal fingerprinting" approach would survive much of McKitrick (2022)’s criticism by enforcing two conditions related to the conduct of the null simulation of the climate model, and the accuracy of the null setting climate model. The conditions we proposed are simpler and easier to verify than those in McKitrick (2022). We provide additional remarks on the residual consistency test in Allen and Tett (1999), showing that it is operational for checking the agreement between the residual covariance matrices of the null simulation and the physical internal variation under certain conditions. We further provide the reason why the Feasible Generalized Least Square method, much advocated by McKitrick (2022), is not regarded as operational by geophysicists.
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Acknowledgements
We thank the reviewers of Climate Dynamics for comments and suggestions which have led to improvement in the presentation, and Hongbin Lin and Shanshan Luo for assistance.
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This research was supported by the National Natural Science Foundation of China Grant 12292983.
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Chen, H., Chen, S.X. & Mu, M. A statistical review on the optimal fingerprinting approach in climate change studies. Clim Dyn 62, 1439–1446 (2024). https://doi.org/10.1007/s00382-023-06975-5
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DOI: https://doi.org/10.1007/s00382-023-06975-5