Reconstructing surface temperature changes over the past 600 years using climate model simulations with data assimilation

Ensemble simulations have been performed with a climate model constrained to follow temperature histories obtained from a recent compilation of 56 well-calibrated surface temperature proxy records, using a new data assimilation technique. First, we demonstrate that the data assimilation technique pr...

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Bibliographic Details
Published in:Journal of Geophysical Research
Main Authors: Goosse, Hugues, Crespin, Elisabeth, de Montety, Anne, Mann, M.E., Renssen, H., Timmermann, A.
Other Authors: UCL - SST/ELI/ELIC - Earth & Climate
Format: Article in Journal/Newspaper
Language:English
Published: American Geophysical Union 2010
Subjects:
Online Access:http://hdl.handle.net/2078.1/33867
https://doi.org/10.1029/2009JD012737
Description
Summary:Ensemble simulations have been performed with a climate model constrained to follow temperature histories obtained from a recent compilation of 56 well-calibrated surface temperature proxy records, using a new data assimilation technique. First, we demonstrate that the data assimilation technique provides a faithful representation in the Northern Hemisphere of the signal recorded by the climate proxies at both the regional and gridbox scales. Second, by varying the external forcing, the parameters of the data assimilation method, and the parameters controlling the equilibrium climate sensitivity of the climate model, we demonstrate that the uncertainty in model results is much lower in simulations using data assimilation than in those without it. This observation implies that the data assimilation, using a set of 56 proxies, is providing an efficient and robust constraint on the simulated climate variability over the past centuries. At the hemispheric and continental scales, the model reconstructions using data assimilation are in good agreement with both the instrumental record of the past 150 years and reconstructions of climate in past centuries derived from the application of traditional statistical approaches to networks of proxy data. This increases the confidence in both the data assimilation and traditional statistical approaches. Our data assimilation method, however, is unable to provide a reliable reconstruction over the North Atlantic Ocean, which we attribute to the paucity of proxy data in that region.