Abstract
Abstract. Two statistical methods are tested to reconstruct the interannual variations in past sea surface temperatures (SSTs) of the North Atlantic (NA) Ocean over the past millennium based on annually resolved and absolutely dated marine proxy records of the bivalve mollusk Arctica islandica. The methods are tested in a pseudo-proxy experiment (PPE) setup using state-of-the-art climate models (CMIP5 Earth system models) and reanalysis data from the COBE2 SST data set. The methods were applied in the virtual reality provided by global climate simulations and reanalysis data to reconstruct the past NA SSTs using pseudo-proxy records that mimic the statistical characteristics and network of Arctica islandica. The multivariate linear regression methods evaluated here are principal component regression and canonical correlation analysis. Differences in the skill of the climate field reconstruction (CFR) are assessed according to different calibration periods and different proxy locations within the NA basin. The choice of the climate model used as a surrogate reality in the PPE has a more profound effect on the CFR skill than the calibration period and the statistical reconstruction method. The differences between the two methods are clearer for the MPI-ESM model due to its higher spatial resolution in the NA basin. The pseudo-proxy results of the CCSM4 model are closer to the pseudo-proxy results based on the reanalysis data set COBE2. Conducting PPEs using noise-contaminated pseudo-proxies instead of noise-free pseudo-proxies is important for the evaluation of the methods, as more spatial differences in the reconstruction skill are revealed. Both methods are appropriate for the reconstruction of the temporal evolution of the NA SSTs, even though they lead to a great loss of variance away from the proxy sites. Under reasonable assumptions about the characteristics of the non-climate noise in the proxy records, our results show that the marine network of Arctica islandica can be used to skillfully reconstruct the spatial patterns of SSTs at the eastern NA basin.
Highlights
The methods are calibrated during the Medieval Period, the Little Ice Age (LIA), the recent period, the industrial period, and the preindustrial period, and the results are shown in the Supplement
The results shown here regard the reconstruction of the industrial period when the regression models are calibrated during the recent period and the LIA (Figs. 1 and 2, respectively) and are shown for the CCSM4 model, the realization r1 of the MPI-Earth system models (ESMs) model, and the COBE2 data
Field correlations are high on the eastern Atlantic basin where less variance loss is observed and a better prediction skill is indicated by the root mean square error (RMSE) and reduction in error (RE)
Summary
Several studies have aimed to reconstruct hemispheric or global average temperature from networks of proxy records (Hegerl et al, 2007; Mann and Jones, 2003; Mann et al, 2008; Marcott et al, 2013; Moberg et al, 2005), as well as large-scale temperature patterns of past changes at global (Mann et al, 2009; Rutherford et al, 2005; Wahl and Ammann, 2007) and regional scale during the last millennium (Ahmed et al, 2013; Büntgen et al, 2017; Esper et al, 2012; Luterbacher et al, 2004; Luterbacher et al, 2016; Xoplaki et al, 2005). Terrestrial proxy records were used by Wang et al (2017) for the reconstruction of a 1200-year AMO index
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