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...

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Published in:Ocean Modelling
Main Authors: Gerber, Markus, Joos, Fortunat
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2013
Subjects:
Online Access:https://boris.unibe.ch/47703/1/1-s2.0-S1463500312001898-main.pdf
https://boris.unibe.ch/47703/
id ftunivbern:oai:boris.unibe.ch:47703
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spelling ftunivbern:oai:boris.unibe.ch:47703 2023-08-20T04:06:55+02:00 An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections Gerber, Markus Joos, Fortunat 2013 application/pdf https://boris.unibe.ch/47703/1/1-s2.0-S1463500312001898-main.pdf https://boris.unibe.ch/47703/ eng eng Elsevier https://boris.unibe.ch/47703/ info:eu-repo/semantics/restrictedAccess Gerber, Markus; Joos, Fortunat (2013). An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections. Ocean Modelling, 64, pp. 29-45. Elsevier 10.1016/j.ocemod.2012.12.012 <http://dx.doi.org/10.1016/j.ocemod.2012.12.012> 530 Physics 550 Earth sciences & geology info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion PeerReviewed 2013 ftunivbern https://doi.org/10.1016/j.ocemod.2012.12.012 2023-07-31T21:05:56Z 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. Article in Journal/Newspaper Greenland Iceland Southern Ocean BORIS (Bern Open Repository and Information System, University of Bern) Greenland Southern Ocean Ocean Modelling 64 29 45
institution Open Polar
collection BORIS (Bern Open Repository and Information System, University of Bern)
op_collection_id ftunivbern
language English
topic 530 Physics
550 Earth sciences & geology
spellingShingle 530 Physics
550 Earth sciences & geology
Gerber, Markus
Joos, Fortunat
An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
topic_facet 530 Physics
550 Earth sciences & geology
description 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.
format Article in Journal/Newspaper
author Gerber, Markus
Joos, Fortunat
author_facet Gerber, Markus
Joos, Fortunat
author_sort Gerber, Markus
title An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
title_short An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
title_full An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
title_fullStr An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
title_full_unstemmed An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections
title_sort ensemble kalman filter multi-tracer assimilation: determining uncertain ocean model parameters for improved climate-carbon cycle projections
publisher Elsevier
publishDate 2013
url https://boris.unibe.ch/47703/1/1-s2.0-S1463500312001898-main.pdf
https://boris.unibe.ch/47703/
geographic Greenland
Southern Ocean
geographic_facet Greenland
Southern Ocean
genre Greenland
Iceland
Southern Ocean
genre_facet Greenland
Iceland
Southern Ocean
op_source Gerber, Markus; Joos, Fortunat (2013). An Ensemble Kalman Filter multi-tracer assimilation: Determining uncertain ocean model parameters for improved climate-carbon cycle projections. Ocean Modelling, 64, pp. 29-45. Elsevier 10.1016/j.ocemod.2012.12.012 <http://dx.doi.org/10.1016/j.ocemod.2012.12.012>
op_relation https://boris.unibe.ch/47703/
op_rights info:eu-repo/semantics/restrictedAccess
op_doi https://doi.org/10.1016/j.ocemod.2012.12.012
container_title Ocean Modelling
container_volume 64
container_start_page 29
op_container_end_page 45
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