CAFE60v1: A 60-Year Large Ensemble Climate Reanalysis. Part II: Evaluation

• Published in: Journal of climate 2021-07, Vol.34 (13), p.5171-5194
• Main Authors: O’Kane, Terence J., Sandery, Paul A., Kitsios, Vassili, Sakov, Pavel, Chamberlain, Matthew A., Squire, Dougal T., Collier, Mark A., Chapman, Christopher C., Fiedler, Russell, Harries, Dylan, Moore, Thomas S., Richardson, Doug, Risbey, James S., Schroeter, Benjamin J. E., Schroeter, Serena, Sloyan, Bernadette M., Tozer, Carly, Watterson, Ian G., Black, Amanda, Quinn, Courtney, Matear, Richard J.
• Format: Article
• Language: English
• Subjects: Air temperature; Anthropogenic factors; Atmosphere; Biogeochemistry; Climate; Climate models; Climate prediction; Climate studies; Climate system; Climate teleconnections; Climate variability; Climatic analysis; Climatic indexes; Data assimilation; El Nino; Empirical analysis; Ensemble forecasting; Estimates; General circulation models; Global climate; Ice observations; Kalman filters; Oceans; Sea ice; Standard deviation; Surface temperature; Surface-air temperature relationships; Temperature; Variability; Weather forecasting
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-20-0518.1

The CSIRO Climate retrospective Analysis and Forecast Ensemble system, version 1 (CAFE60v1) provides a large (96 member) ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spatiotemporal resolutions suitable to enable probabilistic climate studies. Using a variant of the ensemble Kalman filter, 96 climate state estimates are generated over the most recent six decades. These state estimates are constrained by monthly mean ocean, atmosphere, and sea ice observations such that their trajectories track the observed state while enabling estimation of the uncertainties in the approximations to the retrospective mean climate over recent decades. For the atmosphere, we evaluate CAFE60v1 in comparison to empirical indices of the major climate teleconnections and blocking with various reanalysis products. Estimates of the large-scale ocean structure, transports, and biogeochemistry are compared to those derived from gridded observational products and climate model projections (CMIP). Sea ice (extent, concentration, and variability) and land surface (precipitation and surface air temperatures) are also compared to a variety of model and observational products. Our results show that CAFE60v1 is a useful, comprehensive, and unique data resource for studying internal climate variability and predictability, including the recent climate response to anthropogenic forcing on multiyear to decadal time scales.