Comments on “Reconstructing the NH Mean Temperature: Can Underestimation of Trends and Variability Be Avoided?”

In a recent paper, Bo Christiansen presents and discusses ‘‘LOC,’’ a methodology for reconstructing past climate that is based on local regressions between climate proxy time series and instrumental time series (Christiansen 2011, hereafter C11). LOC respects two important scientific facts about proxy data that are often overlooked, namely that many proxies are likely influenced by strictly local temperature, and, to reflect causality, the proxies should be written as functions of climate, not vice versa. There are, however, several weaknesses to the LOC method: uncertainty is not propagated through the multiple stages of the analysis, the effects of observational errors in the instrumental record are not considered, and as the proxies become uninformative of climate, the variance of a reconstruction produced by LOC becomes unbounded—a result that is clearly unphysical. These shortcomings can be overcome by interpreting the LOC method in the context of recently proposed Bayesian hierarchical reconstruction methods. Section 2 reviews the basic modeling assumptions underlying LOC and details the shortcomings of this approach. To illustrate one possible solution to the shortcomings of LOC, section 3 presents a Bayesian interpretation of LOC and briefly describes the connections between LOC and two recently published Bayesian reconstruction methods. Section 4 discusses the variance of the reconstructed series in both the original and Bayesian LOC frameworks, and section 5 provides a few concluding remarks.