Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble
We present an assessment of the probabilistic and climatological consistency of the CMIP5/PMIP3 ensemble simulations for the last millennium relative to proxy-based reconstructions under the paradigm of a statistically indistinguishable ensemble. We evaluate whether simulations and reconstru...
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doaj-bb54b66c474f4f4d868d9a4733a0e42d2020-11-24T23:05:08ZengCopernicus PublicationsClimate of the Past1814-93241814-93322013-11-01962471248710.5194/cp-9-2471-2013Consistency of the multi-model CMIP5/PMIP3-past1000 ensembleO. Bothe0J. H. Jungclaus1D. Zanchettin2Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, GermanyMax Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, GermanyMax Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, GermanyWe present an assessment of the probabilistic and climatological consistency of the CMIP5/PMIP3 ensemble simulations for the last millennium relative to proxy-based reconstructions under the paradigm of a statistically indistinguishable ensemble. We evaluate whether simulations and reconstructions are compatible realizations of the unknown past climate evolution. A lack of consistency is diagnosed in surface air temperature data for the Pacific, European and North Atlantic regions. On the other hand, indications are found that temperature signals partially agree in the western tropical Pacific, the subtropical North Pacific and the South Atlantic. Deviations from consistency may change between sub-periods, and they may include pronounced opposite biases in different sub-periods. These distributional inconsistencies originate mainly from differences in multi-centennial to millennial trends. Since the data uncertainties are only weakly constrained, the frequently too wide ensemble distributions prevent the formal rejection of consistency of the simulation ensemble. The presented multi-model ensemble consistency assessment gives results very similar to a previously discussed single-model ensemble suggesting that structural and parametric uncertainties do not exceed forcing and internal variability uncertainties.http://www.clim-past.net/9/2471/2013/cp-9-2471-2013.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
O. Bothe J. H. Jungclaus D. Zanchettin |
spellingShingle |
O. Bothe J. H. Jungclaus D. Zanchettin Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble Climate of the Past |
author_facet |
O. Bothe J. H. Jungclaus D. Zanchettin |
author_sort |
O. Bothe |
title |
Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble |
title_short |
Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble |
title_full |
Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble |
title_fullStr |
Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble |
title_full_unstemmed |
Consistency of the multi-model CMIP5/PMIP3-past1000 ensemble |
title_sort |
consistency of the multi-model cmip5/pmip3-past1000 ensemble |
publisher |
Copernicus Publications |
series |
Climate of the Past |
issn |
1814-9324 1814-9332 |
publishDate |
2013-11-01 |
description |
We present an assessment of the probabilistic and climatological
consistency of the CMIP5/PMIP3 ensemble simulations for the last
millennium relative to proxy-based reconstructions under the
paradigm of a statistically indistinguishable ensemble. We evaluate
whether simulations and reconstructions are compatible realizations
of the unknown past climate evolution. A lack of consistency is
diagnosed in surface air temperature data for the Pacific, European
and North Atlantic regions. On the other hand, indications are found
that temperature signals partially agree in the western tropical
Pacific, the subtropical North Pacific and the South
Atlantic. Deviations from consistency may change between
sub-periods, and they may include pronounced opposite biases in
different sub-periods. These distributional inconsistencies
originate mainly from differences in multi-centennial to millennial
trends. Since the data uncertainties are only weakly constrained,
the frequently too wide ensemble distributions
prevent the formal rejection of consistency of the simulation ensemble.
The presented multi-model ensemble consistency assessment gives results
very similar to a previously discussed single-model ensemble suggesting
that structural and parametric uncertainties do not exceed forcing and
internal variability uncertainties. |
url |
http://www.clim-past.net/9/2471/2013/cp-9-2471-2013.pdf |
work_keys_str_mv |
AT obothe consistencyofthemultimodelcmip5pmip3past1000ensemble AT jhjungclaus consistencyofthemultimodelcmip5pmip3past1000ensemble AT dzanchettin consistencyofthemultimodelcmip5pmip3past1000ensemble |
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