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Currently available data-assimilation-based reconstructions of past climate variations have only used statistical proxy system models to make the link between climate model outputs and indirect observations from tree rings. However, the linearity and stationarity assumptions of the statistical approach may have limitations. In this study, we incorporate the process-based dendroclimatic model MAIDEN into a data assimilation procedure using the reconstruction of near-surface air temperature, precipitation and winds in the midlatitudes of the Southern Hemisphere over the past 400 years as a test case. We compare our results with a data assimilation approach including a linear regression as a proxy system model for tree-ring width proxies. Overall, when compared to instrumental data, the reconstructions using MAIDEN as a proxy system model offer a skill equivalent to the experiment using the regression model. However, knowing the advantages that a process-based model can bring and the improvements that can still be made with MAIDEN, those results are promising.

Tree-ring widths represent the most commonly used proxy to reconstruct the climate of the last millennium at high resolution, thanks to their large-scale availability. The approach often relies on a relationship between tree-ring width series and climate estimated on the basis of a linear regression. However, the underlying linearity and stationarity assumptions may be inadequate and dendroclimatic process-based models may be able to overcome some of those limitations. In this thesis, we have included for the first time a dendroclimatic process-based model, MAIDEN, into a data assimilation procedure in order to improve large-scale climate reconstructions. We have first developed a protocol to calibrate and apply MAIDEN to potentially any sites with tree-ring width data in the extratropical region. We have shown that MAIDEN can be applied at global scale with a good performance and that the clear benefits obtained make it an appealing candidate for large-scale paleoclimate reconstructions. Subsequently, the MAIDEN model has been successfully incorporated into a data assimilation procedure as a proxy system model allowing a robust comparison of the outputs of an Earth system model with tree-ring width observations. The procedure has been tested to reconstruct the climate variability in the Southern Hemisphere over the last four centuries with encouraging results. Even though additional analysis are needed to fully take advantage of the new development, important steps have been made to demonstrate that using MAIDEN as a proxy system model is a promising way to improve the large-scale climate reconstructions with data assimilation., (SC - Sciences) -- UCL, 2021

Tree-rings are one of the most commonly used proxies for reconstructing past climates at annual resolution. The climate information is generally deduced from tree-rings using statistical relationships, but the assumed linearity and stationarity may be inadequate. Process-based models allow for non-stationarity and non-linearity; however, many challenges are associated with their application for global scale reconstructions. In this study, we aim to test the feasibility of using the mechanistic model MAIDEN at the global scale for paleoclimate reconstructions based on data assimilation by applying it to the PAGES2k tree-ring width database. We also compare its performance with the simpler model VS-Lite, often used in global applications. Both models are skillful in terms of calibration and verification correlations for a similar number of sites (63 and 64 for VS-Lite and MAIDEN, respectively). VS-Lite tends to perform better for sites where the climate signal in tree-rings is strong and clear. By contrast, MAIDEN’s performance is likely mostly limited by the lack of data (for example, daily Gross Primary Production data or phenological timings) needed to accurately calibrate the model. However, when the calibration is robust, both models reproduce well the observed link between climate and tree-growth. In general, VS-Lite tends to overestimate the climate signal in tree-rings compared to MAIDEN, which better reproduces the magnitude of the climate signal on average. Our results show that both models are complementary and can be applied at the global scale to reconstruct past climates using an adequate protocol designed to exploit existing tree-ring data.