Modeling oxygen isotopes in the Pliocene: Large-scale features over the land and ocean
The first isotope-enabled general circulation model (GCM) simulations of the Pliocene are used to discuss the interpretation of δ18O measurements for a warm climate. The model suggests that spatial patterns of Pliocene ocean surface δ18O ( inline image) were similar to those of the preindustrial per...
| Published in: | Paleoceanography |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2015
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| Subjects: | |
| Online Access: | https://eprints.whiterose.ac.uk/90277/ https://eprints.whiterose.ac.uk/90277/7/Tindall_et_al-2015-Paleoceanography.pdf https://doi.org/10.1002/2014PA002774 |
| Summary: | The first isotope-enabled general circulation model (GCM) simulations of the Pliocene are used to discuss the interpretation of δ18O measurements for a warm climate. The model suggests that spatial patterns of Pliocene ocean surface δ18O ( inline image) were similar to those of the preindustrial period; however, Arctic and coastal regions were relatively depleted, while South Atlantic and Mediterranean regions were relatively enriched. Modeled inline image anomalies are closely related to modeled salinity anomalies, which supports using inline image as a paleosalinity proxy. Modeled Pliocene precipitation δ18O ( inline image) was enriched relative to the preindustrial values (but with depletion of <2‰ over some tropical regions). While usually modest (<4‰), the enrichment can reach 25‰ over ice sheet regions. In the tropics inline image anomalies are related to precipitation amount anomalies, although there is usually a spatial offset between the two. This offset suggests that the location of precipitation change is more uncertain than the amplitude when interpreting inline image. At high latitudes inline image anomalies relate to temperature anomalies; however, the relationship is neither linear nor spatially coincident: a large inline image signal does not always translate to a large temperature signal. These results suggest that isotope modeling can lead to enhanced synergy between climate models and climate proxy data. The model can relate proxy data to climate in a physically based way even when the relationship is complex and nonlocal. The δ18O-climate relationships, identified here from a GCM, could not be determined from transfer functions or simple models. |
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