CAFE60 reanalysis
The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large 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 clima...
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Online Access: | https://researchdata.edu.au/cafe60-reanalysis/1674648 |
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ftands:oai:ands.org.au::1674648 2023-05-15T18:17:31+02:00 CAFE60 reanalysis CSIRO (hasAssociationWith) CSIRO (isManagedBy) Terry O'Kane (hasPrincipalInvestigator) Temporal: From 1960-01-01 to 2020-12-10 https://researchdata.edu.au/cafe60-reanalysis/1674648 unknown Commonwealth Scientific and Industrial Research Organisation https://researchdata.edu.au/cafe60-reanalysis/1674648 102.100.100/389002 https://data.csiro.au/dap/ ensemble climate reanalysis data assimilation Climate Change Processes EARTH SCIENCES ATMOSPHERIC SCIENCES Physical Oceanography OCEANOGRAPHY Atmospheric Dynamics collection ftands 2022-12-19T23:58:41Z The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large 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. Strongly coupled data assimilation (SCDA) is implemented via an ensemble transform Kalman filter in order to constrain a general circulation climate model to observations. Satellite (altimetry, sea surface temperature, sea ice concentration) and in situ ocean temperature and salinity profiles are directly assimilated each month, whereas atmospheric observations are sub-sampled from the JRA55 atmospheric reanalysis. Strong coupling is implemented via explicit cross domain covariances between ocean, atmosphere, sea ice and ocean biogeochemistry. Atmospheric and surface ocean fields are available at daily resolution and monthly resolution for the land, subsurface ocean and sea ice. The system also produces a complete data archive of initial conditions potentially enabling individual forecasts for all members each month over the 60 year period. The size of the ensemble and application of strongly coupled data assimilation lead to new insights for future reanalyses. CAFE60v1 has been validated in comparison to empirical indices of the major climate teleconnections and blocking from various reanalysis products (ERA5, JRA55, NCEP NR1). Estimates of the large scale ocean structure and transports have been compared to those derived from gridded observational products (WOA18, HadISST, ERSSTv5) and climate model projections ... Other/Unknown Material Sea ice Research Data Australia (Australian National Data Service - ANDS) Journal of Climate 1 48 |
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Open Polar |
collection |
Research Data Australia (Australian National Data Service - ANDS) |
op_collection_id |
ftands |
language |
unknown |
topic |
ensemble climate reanalysis data assimilation Climate Change Processes EARTH SCIENCES ATMOSPHERIC SCIENCES Physical Oceanography OCEANOGRAPHY Atmospheric Dynamics |
spellingShingle |
ensemble climate reanalysis data assimilation Climate Change Processes EARTH SCIENCES ATMOSPHERIC SCIENCES Physical Oceanography OCEANOGRAPHY Atmospheric Dynamics CAFE60 reanalysis |
topic_facet |
ensemble climate reanalysis data assimilation Climate Change Processes EARTH SCIENCES ATMOSPHERIC SCIENCES Physical Oceanography OCEANOGRAPHY Atmospheric Dynamics |
description |
The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large 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. Strongly coupled data assimilation (SCDA) is implemented via an ensemble transform Kalman filter in order to constrain a general circulation climate model to observations. Satellite (altimetry, sea surface temperature, sea ice concentration) and in situ ocean temperature and salinity profiles are directly assimilated each month, whereas atmospheric observations are sub-sampled from the JRA55 atmospheric reanalysis. Strong coupling is implemented via explicit cross domain covariances between ocean, atmosphere, sea ice and ocean biogeochemistry. Atmospheric and surface ocean fields are available at daily resolution and monthly resolution for the land, subsurface ocean and sea ice. The system also produces a complete data archive of initial conditions potentially enabling individual forecasts for all members each month over the 60 year period. The size of the ensemble and application of strongly coupled data assimilation lead to new insights for future reanalyses. CAFE60v1 has been validated in comparison to empirical indices of the major climate teleconnections and blocking from various reanalysis products (ERA5, JRA55, NCEP NR1). Estimates of the large scale ocean structure and transports have been compared to those derived from gridded observational products (WOA18, HadISST, ERSSTv5) and climate model projections ... |
author2 |
CSIRO (hasAssociationWith) CSIRO (isManagedBy) Terry O'Kane (hasPrincipalInvestigator) |
format |
Other/Unknown Material |
title |
CAFE60 reanalysis |
title_short |
CAFE60 reanalysis |
title_full |
CAFE60 reanalysis |
title_fullStr |
CAFE60 reanalysis |
title_full_unstemmed |
CAFE60 reanalysis |
title_sort |
cafe60 reanalysis |
publisher |
Commonwealth Scientific and Industrial Research Organisation |
url |
https://researchdata.edu.au/cafe60-reanalysis/1674648 |
op_coverage |
Temporal: From 1960-01-01 to 2020-12-10 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
https://data.csiro.au/dap/ |
op_relation |
https://researchdata.edu.au/cafe60-reanalysis/1674648 102.100.100/389002 |
container_title |
Journal of Climate |
container_start_page |
1 |
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48 |
_version_ |
1766191776251510784 |