Session: Cross-cutting Group 2 (Paleovar, Past to future, Data assimilation)
Author: Hugues Goosse / hugues.goosse@uclouvain.be / Universite catholique de Louvain
Co-author: Mike N. Evans, University of Maryland;
                    Samar Khatiwala, University of Oxford;
                    Diane Marie Thompson, Boston University;

Abstract:
Optimally using data assimilation techniques to combine paleoclimate observations and model results requires addressing several challenges. First, the variables measured in environmental archives collected in the field (such as tree ring width or pollen assemblage) are often not directly simulated by climate or Earth system models and may be a complex and nonlinear function of several environmental factors. An objective comparison between the measured variables and simulation results may be improved by modeling the mechanisms by which a paleoclimatic archive is imprinted with an environmental signal, i.e., by using a “proxy system model”. Second, specific data assimilation techniques are needed to handle sparse data, represent temporal averaging, spatial downscaling and chronological uncertainty. In this framework, the goal of the new PAGES working group on Data Assimilation and Proxy System modeling (DAPS; http://pastglobalchanges.org/ini/wg/daps/intro) is to stimulate the application of proxy system models and data assimilation in paleoclimatology. Among the initiatives proposed at the first DAPS meeting in Louvain la Neuve, Belgium, were “proxy system model intercomparison projects” for important paleoclimatic archives and observations, which will lead to improved assessments of proxy system model uncertainty; and application of data assimilation methods to construct a last century product, whose skill and error characteristics may be examined relative to historical and modern reanalyses within the data assimilation framework. These efforts will benefit from close collaboration with the PMIP4 initiative.