An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
An Ensemble Kalman Filter is applied to assimilate observed tracer fields in various combinations in the Bern3D ocean model. Each tracer combination yields a set of optimal transport parameter values that are used in projections with prescribed CO2 stabilization pathways. The assimilation of tempera...
| Published in: | Ocean Modelling |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Elsevier
2013
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| Subjects: | |
| Online Access: | https://boris.unibe.ch/47703/1/1-s2.0-S1463500312001898-main.pdf https://boris.unibe.ch/47703/ |
| Summary: | An Ensemble Kalman Filter is applied to assimilate observed tracer fields in various combinations in the Bern3D ocean model. Each tracer combination yields a set of optimal transport parameter values that are used in projections with prescribed CO2 stabilization pathways. The assimilation of temperature and salinity fields yields a too vigorous ventilation of the thermocline and the deep ocean, whereas the inclusion of CFC-11 and radiocarbon improves the representation of physical and biogeochemical tracers and of ventilation time scales. Projected peak uptake rates and cumulative uptake of CO2 by the ocean are around 20% lower for the parameters determined with CFC-11 and radiocarbon as additional target compared to those with salinity and temperature only. Higher surface temperature changes are simulated in the Greenland–Norwegian–Iceland Sea and in the Southern Ocean when CFC-11 is included in the Ensemble Kalman model tuning. These findings highlights the importance of ocean transport calibration for the design of near-term and long-term CO2 emission mitigation strategies and for climate projections. |
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