. Time and time again I come by folks who push that paper on me. I wish I knew why; I don't. That paper is the "poster child" for the saying "bamboozle them with bullsh*t."
I cannot comment on the other papers you have in mind. Regarding the one you shared,
The main issue with the "A comparison of local and aggregated climate model outputs with observed data" (ACCM) paper is that it is based on a false premise, namely that the selected climate simulations predict (forecast) climate in a deterministic sense. Climate models may indeed be used in a weather forecasting mode, and this is one way of evaluating their sub-grid scale parameterization at the sub-daily time scale. (8.4.11 of
Climate Models and Their Evaluation) Some are even used to “forecast” climate at the decadal scale (
Advancing decadal-scale climate prediction in the North Atlantic Sector) using observed oceanic and atmospheric initial conditions, the oceanic inertia constraining the atmospheric model. However, these experiments are still considered highly experimental (
Prospects for decadal climate prediction) and never claim to correlate with the interannual variability. Climate simulations included in the Intergovernmental Panel on Climate Change’s TAR and AR4 also make no pretence of predicting/forecasting weather or climate. As Doug Smith
et al wrote in "
Improved Surface Temperature Prediction for the Coming Decade from a Global Climate Model," (2007)
Previous climate model projections of climate change accounted for external forcing from natural and anthropogenic sources but did not attempt to predict internally generated natural variability.
Evaluating climate models based on temporal correlations with observations is meaningful only if those models claim to forecast the year-to-year climate variations due to natural variability. The climate simulations analysed by ACCM make no such claim, and the paper’s main conclusion, that models are poor, is irrelevant.
ACCM expected individual models to show some skill in predicting multidecadal climate variations. They do, but their skill is limited to the small fraction of climate’s variability driven by external forcing. To evaluate model performance, it is fundamental to extract the model’s response to the external forcing from the background natural variability (
Climate Models and Their Evaluation). Failing to do this, ACCM have merely shown that climate models display chaotic behaviour at small and long time scales, not that they are poor.
The ACCM paper received three evaluations. Reviewer A provided a solid review which identified unsubstantiated or false claims and methodological shortcomings. The evaluation included a comment on the general lack of rigour of the paper with a recommendation not to publish. Reviewer B rated the paper as “Very good to excellent” and made three superfi- cial suggestions for improvements. Reviewer C rated the paper as “Poor to fair” and specifically stated: “This paper is misleading as it is based on a wrong assumption related to the climate system predictability.” Reviewer C also criticized the methodology as inappropriate and recommended the paper be rejected outright.
Faced with these reviews, Dr Kundzewicz [editor of the journal that published the paper] in his decision letter writes he heeded advice from the late Stephen Schneider (editor of Climatic Change): “When I get a paper that generates controversy and splits reviewer advice, I look to be sure that it is mostly differing philosophy rather than technical errors that underlie the dispute.”
While I certainly agree with this guiding principle, reviewers A and C rejected the paper on technical and methodological grounds, not philosophy. Their review highlights a general lack of rigour, methodological issues and factual errors obvious to anyone familiar with climate science. Although there may be philosophical differences between AKCEM and the critics, this should not be an excuse to dismiss methodological issues. In my experience as author and reviewer, strong opposition to publication by two reviewers out of three generally leads either to rejection, or, if the editor feels the paper has merit, to an additional review. In this case, however, it seems that the critics were not taken seriously, or even understood. Indeed, the editorial piece
Perhaps you care to cite someone's work imbued with intellectual/scientific rigor and wherein the authors at least bother to evaluate the claims a model makes rather than showing how a predictive model does not support claims it does not attempt to make?