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| Titel |
A dynamical reconstruction of the pre-industrial and the LGM ocean state constrained by global δ18O data |
| VerfasserIn |
Charlotte Breitkreuz, Andre Paul, Takasumi Kurahashi-Nakamura, Martin Losch, Michael Schulz |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250140202
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| Publikation (Nr.) |
 EGU/EGU2017-3555.pdf |
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| Zusammenfassung |
| Combining ocean general circulation models with observational data via inverse modeling is
a powerful means to obtain more reliable estimates of the ocean’s state. The Last Glacial
Maximum (19-23 ka BP, LGM) was a climatic state substantially different from today and the
large-scale ocean circulation patterns during this time remain uncertain. It is furthermore
unclear if the sparse data coverage of the LGM is actually sufficient to constrain the ocean
circulation by an inverse modeling technique.
We used the adjoint method to estimate the state of the global ocean. For the
pre-industrial, this estimate is consistent with the dynamics of the MIT general circulation
model (MITgcm) and global temperature, salinity and δ18O data within their respective error
bounds. The model uses a cubed-sphere grid with 192 x 32 horizontal grid cells and 15
vertical levels. A water-isotopes module was used to simulate stable water isotopes such that,
to our knowledge for the first time, global δ18O data from the whole water-column could be
assimilated using the adjoint method. The state estimate based on our 200-year long
optimized run shows significant improvements in comparison to the original forward run
without data constraint (“first guess”). For example, surface δ18O values in the subtropical
gyres in the Atlantic, across the North Atlantic, the Mediterranean Sea and in the
Arctic Oceans show a much better agreement with the observations. The same
holds true for deep-ocean δ18O values, for example in the Atlantic and the Arctic
Oceans.
Two additional state estimates are presented. Firstly, to test the constraint given by the
limited data coverage of the LGM an estimate for the pre-industrial ocean is obtained
constrained only by data equivalent to available LGM data in terms of data types and data
density. Secondly, we reconstruct the state of the LGM ocean using global sea-surface
temperature and δ18O data from benthic and planktonic foraminifera from various sources. |
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