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Climate of the Past An interactive open-access journal of the European Geosciences Union
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Volume 12, issue 7
Clim. Past, 12, 1555–1563, 2016
https://doi.org/10.5194/cp-12-1555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Clim. Past, 12, 1555–1563, 2016
https://doi.org/10.5194/cp-12-1555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Jul 2016

Research article | 21 Jul 2016

Influence of proxy data uncertainty on data assimilation for the past climate

Anastasios Matsikaris1,2, Martin Widmann1, and Johann Jungclaus2 Anastasios Matsikaris et al.
  • 1University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
  • 2Max Planck Institute for Meteorology, Hamburg, Germany

Abstract. Data assimilation (DA) is an emerging topic in palaeoclimatology and one of the key challenges in this field. Assimilating proxy-based continental mean temperature reconstructions into the MPI-ESM model showed a lack of information propagation to small spatial scales . Here, we investigate whether this lack of regional skill is due to the methodology or to errors in the assimilated reconstructions. Error separation is fundamental, as it can lead to improvements in DA methods. We address the question by performing a new set of simulations, using two different sets of target data; the proxy-based PAGES 2K reconstructions (DA-P scheme), and the HadCRUT3v instrumental observations (DA-I scheme). Again, we employ ensemble-member selection DA using the MPI-ESM model, and assimilate Northern Hemisphere (NH) continental mean temperatures; the simulated period is 1850–1949 AD. Both DA schemes follow the large-scale target and observed climate variations well, but the assimilation of instrumental data improves the performance. This improvement cannot be seen for Asia, where the limited instrumental coverage leads to errors in the target data and low skill for the DA-I scheme. No skill on small spatial scales is found for either of the two DA schemes, demonstrating that errors in the assimilated data are not the main reason for the unrealistic representation of the regional temperature variability in Europe and the NH. It can thus be concluded that assimilating continental mean temperatures is not ideal for providing skill on small spatial scales.

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We have assimilated proxy-based (PAGES 2K) and instrumental (HadCRUT3v) observations into a General Circulation Model (MPI-ESM-CR). Assimilating instrumental data improves the performance of Data Assimilation. No skill on small spatial scales is however found for either of the two schemes. Errors in the assimilated data are therefore not the main reason for this lack of skill; continental mean temperatures cannot provide skill on small spatial scales in palaeoclimate reconstructions.
We have assimilated proxy-based (PAGES 2K) and instrumental (HadCRUT3v) observations into a...
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