论文标题
关于气候变化研究中最佳指纹方法的综述
A Review on the Optimal Fingerprinting Approach in Climate Change Studies
论文作者
论文摘要
根据统计推断的观点，根据最近对McKitrick（2021）的批评，我们从Allen and Tett（1999）中总结了“最佳指纹”方法的综述。我们的综述发现，“最佳指纹”方法将在两个条件下麦基特里克（2021）的批评中幸存下来：（i）气候模型的无效模拟与物理观察无关，并且（ii）无效的模拟提供了对物理观察的残留共价矩阵的一致估计，依赖于模型的造型，并依赖于该模型的凝结和质量质量的质量质量。如果后一个条件失败，则估计器仍将在常规条件下保持公正和一致，但失去了方法的“最佳”方面。 Allen和Tett（1999）建议的剩余一致性测试对于检查零模拟的残留协方差与物理观察之间的协议有效。我们进一步概述了“最佳指纹”方法与可行的概括性最小平方之间的联系。
We provide a review on the "optimal fingerprinting" approach as summarized in Allen and Tett (1999) from a point view of statistical inference in light of the recent criticism of McKitrick (2021). Our review finds that the "optimal fingerprinting" approach would survive much of McKitrick (2021)'s criticism under two conditions: (i) the null simulation of the climate model is independent of the physical observations and (ii) the null simulation provides consistent estimation of the residual covariance matrix of the physical observations, both depend on the conduction and the quality of the climate models. If the latter condition fails, the estimator would be still unbiased and consistent under routine conditions, but losing the "optimal" aspect of the approach. The residual consistency test suggested by Allen and Tett (1999) is valid for checking the agreement between the residual covariances of the null simulation and the physical observations. We further outline the connection between the "optimal fingerprinting" approach and the Feasible Generalized Least Square.
