Are paleoclimate model ensembles consistent with the MARGO data synthesis?
We investigate the consistency of various ensembles of climate model simulations with the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) sea surface temperature data synthesis. We discover that while two multi-model ensembles, created through the Paleoclimate Model I...
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Series: | Climate of the Past |
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doaj-62d4c52b1eeb420f87441b9064ecf84c2020-11-24T23:14:47ZengCopernicus PublicationsClimate of the Past1814-93241814-93322011-08-017391793310.5194/cp-7-917-2011Are paleoclimate model ensembles consistent with the MARGO data synthesis?J. C. HargreavesA. PaulR. OhgaitoA. Abe-OuchiJ. D. AnnanWe investigate the consistency of various ensembles of climate model simulations with the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) sea surface temperature data synthesis. We discover that while two multi-model ensembles, created through the Paleoclimate Model Intercomparison Projects (PMIP and PMIP2), pass our simple tests of reliability, an ensemble based on parameter variation in a single model does not perform so well. We show that accounting for observational uncertainty in the MARGO database is of prime importance for correctly evaluating the ensembles. Perhaps surprisingly, the inclusion of a coupled dynamical ocean (compared to the use of a slab ocean) does not appear to cause a wider spread in the sea surface temperature anomalies, but rather causes systematic changes with more heat transported north in the Atlantic. There is weak evidence that the sea surface temperature data may be more consistent with meridional overturning in the North Atlantic being similar for the LGM and the present day. However, the small size of the PMIP2 ensemble prevents any statistically significant results from being obtained.http://www.clim-past.net/7/917/2011/cp-7-917-2011.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
J. C. Hargreaves A. Paul R. Ohgaito A. Abe-Ouchi J. D. Annan |
spellingShingle |
J. C. Hargreaves A. Paul R. Ohgaito A. Abe-Ouchi J. D. Annan Are paleoclimate model ensembles consistent with the MARGO data synthesis? Climate of the Past |
author_facet |
J. C. Hargreaves A. Paul R. Ohgaito A. Abe-Ouchi J. D. Annan |
author_sort |
J. C. Hargreaves |
title |
Are paleoclimate model ensembles consistent with the MARGO data synthesis? |
title_short |
Are paleoclimate model ensembles consistent with the MARGO data synthesis? |
title_full |
Are paleoclimate model ensembles consistent with the MARGO data synthesis? |
title_fullStr |
Are paleoclimate model ensembles consistent with the MARGO data synthesis? |
title_full_unstemmed |
Are paleoclimate model ensembles consistent with the MARGO data synthesis? |
title_sort |
are paleoclimate model ensembles consistent with the margo data synthesis? |
publisher |
Copernicus Publications |
series |
Climate of the Past |
issn |
1814-9324 1814-9332 |
publishDate |
2011-08-01 |
description |
We investigate the consistency of various ensembles of climate model simulations with the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) sea surface temperature data synthesis. We discover that while two multi-model ensembles, created through the Paleoclimate Model Intercomparison Projects (PMIP and PMIP2), pass our simple tests of reliability, an ensemble based on parameter variation in a single model does not perform so well. We show that accounting for observational uncertainty in the MARGO database is of prime importance for correctly evaluating the ensembles. Perhaps surprisingly, the inclusion of a coupled dynamical ocean (compared to the use of a slab ocean) does not appear to cause a wider spread in the sea surface temperature anomalies, but rather causes systematic changes with more heat transported north in the Atlantic. There is weak evidence that the sea surface temperature data may be more consistent with meridional overturning in the North Atlantic being similar for the LGM and the present day. However, the small size of the PMIP2 ensemble prevents any statistically significant results from being obtained. |
url |
http://www.clim-past.net/7/917/2011/cp-7-917-2011.pdf |
work_keys_str_mv |
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