Global reconstruction of surface temperature fields for past equilibrium climates

Paleoclimate simulations are widely used as a test of the ability of climate models to simulate climate states that are substantially different to the present day, and quantitative reconstructions of these climate states is an essential component of model evaluation.  With there being no large network of instrumental observations from these periods, we must rely on inferences from a relatively modest number of unevenly distributed proxy records which are believed to be quantitatively indicative of the climate state.  In order to robustly establish climatic conditions over global scales, we require methods for smoothing and interpolating between these sparse and imperfect estimates.  In recent years, we have worked on this problem and created a global reconstruction of the Last Glacial Maximum [Annan and Hargreaves, 2013, Climate of the Past] using the data and models which were available at that time.  The method uses scaled patterns from the PMIP ensemble of structurally diverse climate simulations, combined with sparse sets of proxy data, to produce spatially coherent and complete  data  fields  for  surface  air  and  sea  temperatures  (potentially  including  the  seasonal cycle)  along  with  uncertainty  estimates  over  the  whole  field.   This  approach  is  more  robust than alternative methods, which either perform a purely statistical interpolation of the data or at best combine the data with a single climate model. Here, we aim to improve the method, update the inputs, and apply the same technique to both Last Glacial Maximum and mid Pliocene climate intervals. As well as generating spatially complete and coherent maps of climate variables, our approach also generates well-calibrated uncertainty estimates.