A Bayesian method for reconstructing climate fields: Development, an application, and possible extensions

We present a Bayesian method for reconstructing climate fields from incomplete (in space and time) instrumental and proxy data sets.
Applying this method to a set of overlapping instrumental and proxy time series produces an ensemble of draws, or realizations, of the spatially and temporally complete climate field each of which is consistent with both the data and the model assumptions. We apply this method to 600 years of high northern latitude temperature proxy data, and use the ensemble to investigate the likelihood that different years or decades featured the warmest or coldest temperatures during the last 600 years. We conclude by discussing a number of possibilities for extending and generalizing the basic reconstruction method used in this analysis.