Observed and simulated estimates of the meridional overturning circulation at 26.5 degrees N in the Atlantic
Daily timeseries of the meridional overturning circulation (MOC) estimated from the UK/US RAPID/MOCHA array at 26.5° [26.5 degrees] N in the Atlantic are used to evaluate the MOC as simulated in two global circulation models: (I) an 8-member ensemble of the coupled climate model ECHAM5/MPI-OM, and (...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
European Geosciences Union / Copernicus
2011
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| Online Access: | http://hdl.handle.net/1721.1/65382 https://orcid.org/0000-0003-3925-6161 |
| Summary: | Daily timeseries of the meridional overturning circulation (MOC) estimated from the UK/US RAPID/MOCHA array at 26.5° [26.5 degrees] N in the Atlantic are used to evaluate the MOC as simulated in two global circulation models: (I) an 8-member ensemble of the coupled climate model ECHAM5/MPI-OM, and (II) the ECCO-GODAE state estimate. In ECHAM5/MPI-OM, we find that the observed and simulated MOC have a similar variability and time-mean within the 99% confidence interval. In ECCO-GODAE, we find that the observed and simulated MOC show a significant correlation within the 99% confidence interval. To investigate the contribution of the different transport components, the MOC is decomposed into Florida Current, Ekman and mid-ocean transports. In both models, the mid-ocean transport is closely approximated by the residual of the MOC minus Florida Current and Ekman transports. As the models conserve volume by definition, future comparisons of the RAPID/MOCHA mid-ocean transport should be done against the residual transport in the models. The similarity in the variance and the correlation between the RAPID/MOCHA, and respectively ECHAM5/MPI-OM and ECCO-GODAE MOC estimates at 26.5° [26.5 degrees] N is encouraging in the context of estimating (natural) variability in climate simulations and its use in climate change signal-to-noise detection analyses. Enhanced confidence in simulated hydrographic and transport variability will require longer observational time series. |
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