CAFE60v1: A 60-year large ensemble climate reanalysis. Part II: Evaluation

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  • 1 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 2 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 3 CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia, and Laboratory for Turbulence Research in Aerospace and Combustion, Department of Mechanical and Aerospace Engineering Monash University, Clayton, Victoria 3800, Australia
  • 4 Bureau of Meteorology, Docklands, Victoria, Australia
  • 5 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 6 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 7 CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
  • 8 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 9 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 10 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 11 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 12 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 13 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 14 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 15 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 16 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 17 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 18 CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
  • 19 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 20 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 21 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
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Abstract

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 spatio-temporal 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 multi-year to decadal time scales.

Corresponding author address: CSIRO Oceans and Atmosphere, Hobart, Tasmania. E-mail: terence.okane@csiro.au

Abstract

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 spatio-temporal 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 multi-year to decadal time scales.

Corresponding author address: CSIRO Oceans and Atmosphere, Hobart, Tasmania. E-mail: terence.okane@csiro.au
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