Preprints
https://doi.org/10.5194/cpd-11-4159-2015
https://doi.org/10.5194/cpd-11-4159-2015

  01 Sep 2015

01 Sep 2015

Review status: this preprint was under review for the journal CP but the revision was not accepted.

The Paleoclimate reanalysis project

S. A. Browning and I. D. Goodwin S. A. Browning and I. D. Goodwin
  • Marine Climate Risk Group, Department of Environmental Sciences, Macquarie University, North Ryde, Australia

Abstract. Recent advances in proxy-model data assimilation have made feasible the development of proxy-based reanalyses. Proxy-based reanalyses aim to make optimum use of both proxy and model data while presenting paleoclimate information in an accessible format – they will undoubtedly play a pivotal role in the future of paleoclimate research. In the Paleoclimate Reanalysis Project (PaleoR) we use "off-line" data assimilation to constrain the CESM1 (CAM5) Last Millennial Ensemble (LME) simulation with a globally distributed multivariate proxy dataset, producing a decadal resolution reanalysis of the past millennium. Discrete time periods are "reconstructed" by using anomalous (±0.5σ) proxy climate signals to select an ensemble of climate state analogues from the LME. Prior to assimilation the LME simulates internal variability that is temporally inconsistent with information from the proxy archive. After assimilation the LME is highly correlated to almost all included proxy data, and dynamical relationships between modelled variables are preserved; thus providing a "real-world" view of climate system evolution during the past millennium. Unlike traditional regression based approaches to paleoclimatology, PaleoR is unaffected by temporal variations in teleconnection patterns. Indices representing major modes of global ocean–atmosphere climate variability can be calculated directly from PaleoR spatial fields. PaleoR derived ENSO, SAM, and NAO indices are consistent with observations and published multiproxy reconstructions. The computational efficiency of "off-line" data assimilation allows easy incorporation and evaluation of new proxy data, and experimentation with different setups and model simulations. PaleoR spatial fields can be viewed online at http://climatefutures.mq.edu.au/research/themes/marine/paleor/.

S. A. Browning and I. D. Goodwin

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

S. A. Browning and I. D. Goodwin

S. A. Browning and I. D. Goodwin

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Short summary
A new global paleoclimate reanalysis (PaleoR) of the past 1200 years is presented. Proxy-data assimilation is used to combine multivariate proxy data with an ensemble simulation of the last millennium. This approach overcomes many constraints facing regression-based paleoclimate approaches by not relying on stable teleconnections through time. Full spatial fields are produced across multiple dynamically consistent variables and have been applied to investigate long-term climate variability.