  We describe a method for reconstructing spatially explicit maps of seasonal
palaeoclimate variables from site-based reconstructions. Using a 3D-Variational
technique, the method finds the best statistically unbiased, and spatially
continuous, estimate of the palaeoclimate anomalies through combining the
site-based reconstructions and a prior estimate of the palaeoclimate state. By
assuming a set of correlations in the error of the prior, the resulting climate
is smoothed both from month to month and from grid cell to grid cell. The
amount of smoothing can be controlled through the choice of two length-scale
values. The method is applied to a set of reconstructions of the climate of the
Last Glacial Maximum (ca. 21,000 years ago, yr BP) for southern Europe derived
from pollen data with a prior derived from results from the third phase of the
Palaeoclimate Intercomparison Project (PMIP3). We demonstrate how to choose
suitable values for the smoothing length scales from the datasets used in the
reconstruction.
