Stable water isotopes in the MITgcm
We present the first results of the implementation of stable water isotopes in the Massachusetts Institute of Technology general circulation model (MITgcm). The model is forced with the isotopic content of precipitation and water vapor from an atmospheric general circulation model (NCAR IsoCAM), whi...
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Copernicus Publications (EGU)
2017
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ftoceanrep:oai:oceanrep.geomar.de:44280 2023-05-15T15:08:14+02:00 Stable water isotopes in the MITgcm Völpel, Rike Paul, André Krandick, Annegret Mulitza, Stefan Schulz, Michael 2017-08-25 text https://oceanrep.geomar.de/id/eprint/44280/ https://oceanrep.geomar.de/id/eprint/44280/1/gmd-10-3125-2017.pdf https://doi.org/10.5194/gmd-10-3125-2017 en eng Copernicus Publications (EGU) https://oceanrep.geomar.de/id/eprint/44280/1/gmd-10-3125-2017.pdf Völpel, R., Paul, A., Krandick, A., Mulitza, S. and Schulz, M. (2017) Stable water isotopes in the MITgcm. Open Access Geoscientific Model Development, 10 (8). pp. 3125-3144. DOI 10.5194/gmd-10-3125-2017 <https://doi.org/10.5194/gmd-10-3125-2017>. doi:10.5194/gmd-10-3125-2017 cc_by_3.0 info:eu-repo/semantics/openAccess Article PeerReviewed 2017 ftoceanrep https://doi.org/10.5194/gmd-10-3125-2017 2023-04-07T15:41:22Z We present the first results of the implementation of stable water isotopes in the Massachusetts Institute of Technology general circulation model (MITgcm). The model is forced with the isotopic content of precipitation and water vapor from an atmospheric general circulation model (NCAR IsoCAM), while the fractionation during evaporation is treated explicitly in the MITgcm. Results of the equilibrium simulation under pre-industrial conditions are compared to observational data and measurements of plankton tow records (the oxygen isotopic composition of planktic foraminiferal calcite). The broad patterns and magnitude of the stable water isotopes in annual mean seawater are well captured in the model, both at the sea surface as well as in the deep ocean. However, the surface water in the Arctic Ocean is not depleted enough, due to the absence of highly depleted precipitation and snowfall. A model–data mismatch is also recognizable in the isotopic composition of the seawater–salinity relationship in midlatitudes that is mainly caused by the coarse grid resolution. Deep-ocean characteristics of the vertical water mass distribution in the Atlantic Ocean closely resemble observational data. The reconstructed δ18Oc at the sea surface shows a good agreement with measurements. However, the model–data fit is weaker when individual species are considered and deviations are most likely attributable to the habitat depth of the foraminifera. Overall, the newly developed stable water isotope package opens wide prospects for long-term simulations in a paleoclimatic context. Article in Journal/Newspaper Arctic Arctic Ocean Foraminifera* OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel) Arctic Arctic Ocean Geoscientific Model Development 10 8 3125 3144 |
institution |
Open Polar |
collection |
OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel) |
op_collection_id |
ftoceanrep |
language |
English |
description |
We present the first results of the implementation of stable water isotopes in the Massachusetts Institute of Technology general circulation model (MITgcm). The model is forced with the isotopic content of precipitation and water vapor from an atmospheric general circulation model (NCAR IsoCAM), while the fractionation during evaporation is treated explicitly in the MITgcm. Results of the equilibrium simulation under pre-industrial conditions are compared to observational data and measurements of plankton tow records (the oxygen isotopic composition of planktic foraminiferal calcite). The broad patterns and magnitude of the stable water isotopes in annual mean seawater are well captured in the model, both at the sea surface as well as in the deep ocean. However, the surface water in the Arctic Ocean is not depleted enough, due to the absence of highly depleted precipitation and snowfall. A model–data mismatch is also recognizable in the isotopic composition of the seawater–salinity relationship in midlatitudes that is mainly caused by the coarse grid resolution. Deep-ocean characteristics of the vertical water mass distribution in the Atlantic Ocean closely resemble observational data. The reconstructed δ18Oc at the sea surface shows a good agreement with measurements. However, the model–data fit is weaker when individual species are considered and deviations are most likely attributable to the habitat depth of the foraminifera. Overall, the newly developed stable water isotope package opens wide prospects for long-term simulations in a paleoclimatic context. |
format |
Article in Journal/Newspaper |
author |
Völpel, Rike Paul, André Krandick, Annegret Mulitza, Stefan Schulz, Michael |
spellingShingle |
Völpel, Rike Paul, André Krandick, Annegret Mulitza, Stefan Schulz, Michael Stable water isotopes in the MITgcm |
author_facet |
Völpel, Rike Paul, André Krandick, Annegret Mulitza, Stefan Schulz, Michael |
author_sort |
Völpel, Rike |
title |
Stable water isotopes in the MITgcm |
title_short |
Stable water isotopes in the MITgcm |
title_full |
Stable water isotopes in the MITgcm |
title_fullStr |
Stable water isotopes in the MITgcm |
title_full_unstemmed |
Stable water isotopes in the MITgcm |
title_sort |
stable water isotopes in the mitgcm |
publisher |
Copernicus Publications (EGU) |
publishDate |
2017 |
url |
https://oceanrep.geomar.de/id/eprint/44280/ https://oceanrep.geomar.de/id/eprint/44280/1/gmd-10-3125-2017.pdf https://doi.org/10.5194/gmd-10-3125-2017 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Foraminifera* |
genre_facet |
Arctic Arctic Ocean Foraminifera* |
op_relation |
https://oceanrep.geomar.de/id/eprint/44280/1/gmd-10-3125-2017.pdf Völpel, R., Paul, A., Krandick, A., Mulitza, S. and Schulz, M. (2017) Stable water isotopes in the MITgcm. Open Access Geoscientific Model Development, 10 (8). pp. 3125-3144. DOI 10.5194/gmd-10-3125-2017 <https://doi.org/10.5194/gmd-10-3125-2017>. doi:10.5194/gmd-10-3125-2017 |
op_rights |
cc_by_3.0 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/gmd-10-3125-2017 |
container_title |
Geoscientific Model Development |
container_volume |
10 |
container_issue |
8 |
container_start_page |
3125 |
op_container_end_page |
3144 |
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1766339630413643776 |