Journal cover Journal topic
Climate of the Past An interactive open-access journal of the European Geosciences Union
doi:10.5194/cp-2016-129
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
06 Dec 2016
Review status
A revision of this discussion paper was accepted for the journal Climate of the Past (CP) and is expected to appear here in due course.
Reconstructing past climate by using proxy data and a linear climate model
Walter A. Perkins and Gregory J. Hakim University of Washington, Seattle, WA, USA
Abstract. We examine the skill of a new approach to climate field reconstructions (CFRs) using an online paleoclimate data assimilation (PDA) method. Several recent studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs), and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational cost by employing an empirical forecast model (linear inverse model; LIM), which has been shown to have comparable skill to CGCMs. We reconstruct annual-average 2 m air temperature over the instrumental period (1850–2000) using proxy records from the Pages 2k Consortium phase 1 database; proxy system models for estimating proxy observations are calibrated on GISTEMP surface temperature analyses. We compare results for LIMs calibrated on observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data relative to a control offline reconstruction method. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial fields and global mean temperature (GMT). Specifically, the coefficient of efficiency (CE) skill metric for detrended GMT increases by an average of 57 % over the offline benchmark. LIM experiments display a common pattern of skill improvement in the spatial fields over northern hemisphere land areas and in the high-latitude North Atlantic – Barents Sea corridor. Experiments for non-CGCM-calibrated LIMs reveal region-specific reductions in spatial skill compared to the offline control, likely due to aspects of the LIM calibration process. Overall, the CGCM-calibrated LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the dynamical evolution, and not simply persistence of temperature anomalies.

Citation: Perkins, W. A. and Hakim, G. J.: Reconstructing past climate by using proxy data and a linear climate model, Clim. Past Discuss., doi:10.5194/cp-2016-129, in review, 2016.
Walter A. Perkins and Gregory J. Hakim
Walter A. Perkins and Gregory J. Hakim
Walter A. Perkins and Gregory J. Hakim

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Short summary
We examine the skill of a novel data assimilation approach to paleoclimate reconstruction that uses linear climate model forecasts. Many reconstruction studies forego the use of forecasts from climate models due to their high computational expense and relatively low skill. We show that the use of simpler linear models can improve reconstruction skill for both global mean temperature and spatial fields. Improvements displayed seem to be related to dynamical information from the forecasts.
We examine the skill of a novel data assimilation approach to paleoclimate reconstruction that...
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