A First Intercomparison of the Simulated LGM Carbon Results Within PMIP‐Carbon: Role of the Ocean Boundary Conditions
Model intercomparison studies of coupled carbon‐climate simulations have the potential to improve our understanding of the processes explaining the pCO2 drawdown at the Last Glacial Maximum (LGM) and to identify related model biases. Models participating in the Paleoclimate Modeling Intercomparison...
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creator | Lhardy, F. Bouttes, N. Roche, D. M. Abe‐Ouchi, A. Chase, Z. Crichton, K. A. Ilyina, T. Ivanovic, R. Jochum, M. Kageyama, M. Kobayashi, H. Liu, B. Menviel, L. Muglia, J. Nuterman, R. Oka, A. Vettoretti, G. Yamamoto, A. |
description | Model intercomparison studies of coupled carbon‐climate simulations have the potential to improve our understanding of the processes explaining the pCO2 drawdown at the Last Glacial Maximum (LGM) and to identify related model biases. Models participating in the Paleoclimate Modeling Intercomparison Project (PMIP) now frequently include the carbon cycle. The ongoing PMIP‐carbon project provides the first opportunity to conduct multimodel comparisons of simulated carbon content for the LGM time window. However, such a study remains challenging due to differing implementation of ocean boundary conditions (e.g., bathymetry and coastlines reflecting the low sea level) and to various associated adjustments of biogeochemical variables (i.e., alkalinity, nutrients, dissolved inorganic carbon). After assessing the ocean volume of PMIP models at the pre‐industrial and LGM, we investigate the impact of these modeling choices on the simulated carbon at the global scale, using both PMIP‐carbon model outputs and sensitivity tests with the iLOVECLIM model. We show that the carbon distribution in reservoirs is significantly affected by the choice of ocean boundary conditions in iLOVECLIM. In particular, our simulations demonstrate a ∼250 GtC effect of an alkalinity adjustment on carbon sequestration in the ocean. Finally, we observe that PMIP‐carbon models with a freely evolving CO2 and no additional glacial mechanisms do not simulate the pCO2 drawdown at the LGM (with concentrations as high as 313, 331, and 315 ppm), especially if they use a low ocean volume. Our findings suggest that great care should be taken on accounting for large bathymetry changes in models including the carbon cycle.
Key Points
Ocean volume is a dominant control on Last Glacial Maximum (LGM) carbon sequestration and must be accurately represented in models
Adjusting the alkalinity to account for the relative change of volume at the LGM induces a large increase of oceanic carbon (of ∼250 GtC)
Paleoclimate Modeling Intercomparison Project‐carbon models standardly simulate high LGM CO2 levels (over 300 ppm) despite a larger proportion of carbon in the ocean at LGM than pre‐industrial |
doi_str_mv | 10.1029/2021PA004302 |
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Key Points
Ocean volume is a dominant control on Last Glacial Maximum (LGM) carbon sequestration and must be accurately represented in models
Adjusting the alkalinity to account for the relative change of volume at the LGM induces a large increase of oceanic carbon (of ∼250 GtC)
Paleoclimate Modeling Intercomparison Project‐carbon models standardly simulate high LGM CO2 levels (over 300 ppm) despite a larger proportion of carbon in the ocean at LGM than pre‐industrial</description><identifier>ISSN: 2572-4517</identifier><identifier>ISSN: 2572-4525</identifier><identifier>EISSN: 2572-4525</identifier><identifier>EISSN: 1944-9186</identifier><identifier>DOI: 10.1029/2021PA004302</identifier><language>eng</language><publisher>Hoboken: Blackwell Publishing Ltd</publisher><subject>Alkalinity ; atmospheric CO2 ; Bathymeters ; Bathymetry ; Boundary conditions ; Carbon ; Carbon content ; Carbon cycle ; Carbon dioxide ; Carbon sequestration ; climate models ; Continental interfaces, environment ; Dissolved inorganic carbon ; Drawdown ; glacial‐interglacial cycles ; Intercomparison ; Last Glacial Maximum ; Modelling ; Nutrients ; Ocean models ; ocean volume ; Ocean, Atmosphere ; Oceans ; Paleoclimate ; Sciences of the Universe ; Sea level ; Simulation ; Windows (intervals)</subject><ispartof>Paleoceanography and Paleoclimatology, 2021-10, Vol.36 (10), p.n/a</ispartof><rights>2021. American Geophysical Union. All Rights Reserved.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4689-66172896c10bc8c4a84ca25c8bb3ccf5392a60385710b93f6a4ec422db569b4c3</citedby><cites>FETCH-LOGICAL-a4689-66172896c10bc8c4a84ca25c8bb3ccf5392a60385710b93f6a4ec422db569b4c3</cites><orcidid>0000-0002-5068-1591 ; 0000-0002-7805-6018 ; 0000-0002-7949-6090 ; 0000-0001-6694-8695 ; 0000-0002-7111-2048 ; 0000-0001-8748-0438 ; 0000-0003-1745-5952 ; 0000-0002-0272-0488 ; 0000-0002-8260-2907 ; 0000-0001-5060-779X ; 0000-0003-1774-3460 ; 0000-0002-3475-4842 ; 0000-0001-6272-9428 ; 0000-0003-0822-5880</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2021PA004302$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2021PA004302$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://hal.science/hal-03358990$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Lhardy, F.</creatorcontrib><creatorcontrib>Bouttes, N.</creatorcontrib><creatorcontrib>Roche, D. M.</creatorcontrib><creatorcontrib>Abe‐Ouchi, A.</creatorcontrib><creatorcontrib>Chase, Z.</creatorcontrib><creatorcontrib>Crichton, K. A.</creatorcontrib><creatorcontrib>Ilyina, T.</creatorcontrib><creatorcontrib>Ivanovic, R.</creatorcontrib><creatorcontrib>Jochum, M.</creatorcontrib><creatorcontrib>Kageyama, M.</creatorcontrib><creatorcontrib>Kobayashi, H.</creatorcontrib><creatorcontrib>Liu, B.</creatorcontrib><creatorcontrib>Menviel, L.</creatorcontrib><creatorcontrib>Muglia, J.</creatorcontrib><creatorcontrib>Nuterman, R.</creatorcontrib><creatorcontrib>Oka, A.</creatorcontrib><creatorcontrib>Vettoretti, G.</creatorcontrib><creatorcontrib>Yamamoto, A.</creatorcontrib><title>A First Intercomparison of the Simulated LGM Carbon Results Within PMIP‐Carbon: Role of the Ocean Boundary Conditions</title><title>Paleoceanography and Paleoclimatology</title><description>Model intercomparison studies of coupled carbon‐climate simulations have the potential to improve our understanding of the processes explaining the pCO2 drawdown at the Last Glacial Maximum (LGM) and to identify related model biases. Models participating in the Paleoclimate Modeling Intercomparison Project (PMIP) now frequently include the carbon cycle. The ongoing PMIP‐carbon project provides the first opportunity to conduct multimodel comparisons of simulated carbon content for the LGM time window. However, such a study remains challenging due to differing implementation of ocean boundary conditions (e.g., bathymetry and coastlines reflecting the low sea level) and to various associated adjustments of biogeochemical variables (i.e., alkalinity, nutrients, dissolved inorganic carbon). After assessing the ocean volume of PMIP models at the pre‐industrial and LGM, we investigate the impact of these modeling choices on the simulated carbon at the global scale, using both PMIP‐carbon model outputs and sensitivity tests with the iLOVECLIM model. We show that the carbon distribution in reservoirs is significantly affected by the choice of ocean boundary conditions in iLOVECLIM. In particular, our simulations demonstrate a ∼250 GtC effect of an alkalinity adjustment on carbon sequestration in the ocean. Finally, we observe that PMIP‐carbon models with a freely evolving CO2 and no additional glacial mechanisms do not simulate the pCO2 drawdown at the LGM (with concentrations as high as 313, 331, and 315 ppm), especially if they use a low ocean volume. Our findings suggest that great care should be taken on accounting for large bathymetry changes in models including the carbon cycle.
Key Points
Ocean volume is a dominant control on Last Glacial Maximum (LGM) carbon sequestration and must be accurately represented in models
Adjusting the alkalinity to account for the relative change of volume at the LGM induces a large increase of oceanic carbon (of ∼250 GtC)
Paleoclimate Modeling Intercomparison Project‐carbon models standardly simulate high LGM CO2 levels (over 300 ppm) despite a larger proportion of carbon in the ocean at LGM than pre‐industrial</description><subject>Alkalinity</subject><subject>atmospheric CO2</subject><subject>Bathymeters</subject><subject>Bathymetry</subject><subject>Boundary conditions</subject><subject>Carbon</subject><subject>Carbon content</subject><subject>Carbon cycle</subject><subject>Carbon dioxide</subject><subject>Carbon sequestration</subject><subject>climate models</subject><subject>Continental interfaces, environment</subject><subject>Dissolved inorganic carbon</subject><subject>Drawdown</subject><subject>glacial‐interglacial cycles</subject><subject>Intercomparison</subject><subject>Last Glacial Maximum</subject><subject>Modelling</subject><subject>Nutrients</subject><subject>Ocean models</subject><subject>ocean volume</subject><subject>Ocean, Atmosphere</subject><subject>Oceans</subject><subject>Paleoclimate</subject><subject>Sciences of the Universe</subject><subject>Sea level</subject><subject>Simulation</subject><subject>Windows (intervals)</subject><issn>2572-4517</issn><issn>2572-4525</issn><issn>2572-4525</issn><issn>1944-9186</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kc1KxDAUhYsoOIzufICAK8FqfjuJuzo4OlCZ4g8uQ5qmTKTTjEmruPMRfEafxA7VwZWre7nnu4cDJ4qOEDxDEItzDDHKUwgpgXgnGmE2wTFlmO1udzTZjw5DeIYQIkEox2IUvaVgZn1owbxpjddutVbeBtcAV4F2acC9XXW1ak0JsutbMFW-6LU7E7q6DeDJtkvbgPx2nn99fA7iBbhztfl9X2ijGnDpuqZU_h1MXVPa1romHER7laqDOfyZ4-hxdvUwvYmzxfV8mmaxogkXcZKgCeYi0QgWmmuqONUKM82LgmhdMSKwSiDhbNIDglSJokZTjMuCJaKgmoyjk8F3qWq59nbVx5BOWXmTZnJzg4QwLgR8RT17PLBr7146E1r57Drf9PEkZjwhDDEEe-p0oLR3IXhTbW0RlJsm5N8mepwM-Jutzfu_rMzTbIER5IJ8A-WIiEs</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Lhardy, F.</creator><creator>Bouttes, N.</creator><creator>Roche, D. 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M. ; Abe‐Ouchi, A. ; Chase, Z. ; Crichton, K. A. ; Ilyina, T. ; Ivanovic, R. ; Jochum, M. ; Kageyama, M. ; Kobayashi, H. ; Liu, B. ; Menviel, L. ; Muglia, J. ; Nuterman, R. ; Oka, A. ; Vettoretti, G. ; Yamamoto, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4689-66172896c10bc8c4a84ca25c8bb3ccf5392a60385710b93f6a4ec422db569b4c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Alkalinity</topic><topic>atmospheric CO2</topic><topic>Bathymeters</topic><topic>Bathymetry</topic><topic>Boundary conditions</topic><topic>Carbon</topic><topic>Carbon content</topic><topic>Carbon cycle</topic><topic>Carbon dioxide</topic><topic>Carbon sequestration</topic><topic>climate models</topic><topic>Continental interfaces, environment</topic><topic>Dissolved inorganic carbon</topic><topic>Drawdown</topic><topic>glacial‐interglacial cycles</topic><topic>Intercomparison</topic><topic>Last Glacial Maximum</topic><topic>Modelling</topic><topic>Nutrients</topic><topic>Ocean models</topic><topic>ocean volume</topic><topic>Ocean, Atmosphere</topic><topic>Oceans</topic><topic>Paleoclimate</topic><topic>Sciences of the Universe</topic><topic>Sea level</topic><topic>Simulation</topic><topic>Windows (intervals)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lhardy, F.</creatorcontrib><creatorcontrib>Bouttes, N.</creatorcontrib><creatorcontrib>Roche, D. 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A.</creatorcontrib><creatorcontrib>Ilyina, T.</creatorcontrib><creatorcontrib>Ivanovic, R.</creatorcontrib><creatorcontrib>Jochum, M.</creatorcontrib><creatorcontrib>Kageyama, M.</creatorcontrib><creatorcontrib>Kobayashi, H.</creatorcontrib><creatorcontrib>Liu, B.</creatorcontrib><creatorcontrib>Menviel, L.</creatorcontrib><creatorcontrib>Muglia, J.</creatorcontrib><creatorcontrib>Nuterman, R.</creatorcontrib><creatorcontrib>Oka, A.</creatorcontrib><creatorcontrib>Vettoretti, G.</creatorcontrib><creatorcontrib>Yamamoto, A.</creatorcontrib><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Paleoceanography and Paleoclimatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lhardy, F.</au><au>Bouttes, N.</au><au>Roche, D. M.</au><au>Abe‐Ouchi, A.</au><au>Chase, Z.</au><au>Crichton, K. A.</au><au>Ilyina, T.</au><au>Ivanovic, R.</au><au>Jochum, M.</au><au>Kageyama, M.</au><au>Kobayashi, H.</au><au>Liu, B.</au><au>Menviel, L.</au><au>Muglia, J.</au><au>Nuterman, R.</au><au>Oka, A.</au><au>Vettoretti, G.</au><au>Yamamoto, A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A First Intercomparison of the Simulated LGM Carbon Results Within PMIP‐Carbon: Role of the Ocean Boundary Conditions</atitle><jtitle>Paleoceanography and Paleoclimatology</jtitle><date>2021-10</date><risdate>2021</risdate><volume>36</volume><issue>10</issue><epage>n/a</epage><issn>2572-4517</issn><issn>2572-4525</issn><eissn>2572-4525</eissn><eissn>1944-9186</eissn><abstract>Model intercomparison studies of coupled carbon‐climate simulations have the potential to improve our understanding of the processes explaining the pCO2 drawdown at the Last Glacial Maximum (LGM) and to identify related model biases. Models participating in the Paleoclimate Modeling Intercomparison Project (PMIP) now frequently include the carbon cycle. The ongoing PMIP‐carbon project provides the first opportunity to conduct multimodel comparisons of simulated carbon content for the LGM time window. However, such a study remains challenging due to differing implementation of ocean boundary conditions (e.g., bathymetry and coastlines reflecting the low sea level) and to various associated adjustments of biogeochemical variables (i.e., alkalinity, nutrients, dissolved inorganic carbon). After assessing the ocean volume of PMIP models at the pre‐industrial and LGM, we investigate the impact of these modeling choices on the simulated carbon at the global scale, using both PMIP‐carbon model outputs and sensitivity tests with the iLOVECLIM model. We show that the carbon distribution in reservoirs is significantly affected by the choice of ocean boundary conditions in iLOVECLIM. In particular, our simulations demonstrate a ∼250 GtC effect of an alkalinity adjustment on carbon sequestration in the ocean. Finally, we observe that PMIP‐carbon models with a freely evolving CO2 and no additional glacial mechanisms do not simulate the pCO2 drawdown at the LGM (with concentrations as high as 313, 331, and 315 ppm), especially if they use a low ocean volume. Our findings suggest that great care should be taken on accounting for large bathymetry changes in models including the carbon cycle.
Key Points
Ocean volume is a dominant control on Last Glacial Maximum (LGM) carbon sequestration and must be accurately represented in models
Adjusting the alkalinity to account for the relative change of volume at the LGM induces a large increase of oceanic carbon (of ∼250 GtC)
Paleoclimate Modeling Intercomparison Project‐carbon models standardly simulate high LGM CO2 levels (over 300 ppm) despite a larger proportion of carbon in the ocean at LGM than pre‐industrial</abstract><cop>Hoboken</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2021PA004302</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-5068-1591</orcidid><orcidid>https://orcid.org/0000-0002-7805-6018</orcidid><orcidid>https://orcid.org/0000-0002-7949-6090</orcidid><orcidid>https://orcid.org/0000-0001-6694-8695</orcidid><orcidid>https://orcid.org/0000-0002-7111-2048</orcidid><orcidid>https://orcid.org/0000-0001-8748-0438</orcidid><orcidid>https://orcid.org/0000-0003-1745-5952</orcidid><orcidid>https://orcid.org/0000-0002-0272-0488</orcidid><orcidid>https://orcid.org/0000-0002-8260-2907</orcidid><orcidid>https://orcid.org/0000-0001-5060-779X</orcidid><orcidid>https://orcid.org/0000-0003-1774-3460</orcidid><orcidid>https://orcid.org/0000-0002-3475-4842</orcidid><orcidid>https://orcid.org/0000-0001-6272-9428</orcidid><orcidid>https://orcid.org/0000-0003-0822-5880</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Alkalinity atmospheric CO2 Bathymeters Bathymetry Boundary conditions Carbon Carbon content Carbon cycle Carbon dioxide Carbon sequestration climate models Continental interfaces, environment Dissolved inorganic carbon Drawdown glacial‐interglacial cycles Intercomparison Last Glacial Maximum Modelling Nutrients Ocean models ocean volume Ocean, Atmosphere Oceans Paleoclimate Sciences of the Universe Sea level Simulation Windows (intervals) |
title | A First Intercomparison of the Simulated LGM Carbon Results Within PMIP‐Carbon: Role of the Ocean Boundary Conditions |
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