Constraining ocean diffusivity from the 8.2 ka event
Greenland ice-core data containing the 8.2 ka event are utilized by a model-data intercomparison within the Earth system model of intermediate complexity, CLIMBER-2.3 to investigate their potential for constraining the range of uncertain ocean diffusivity properties. Within a stochastic version of t...
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ftleibnizopen:oai:oai.leibnizopen.de:KOQqsIYBdbrxVwz6u3kl 2023-05-15T15:11:09+02:00 Constraining ocean diffusivity from the 8.2 ka event Lorenz, A. Held, H. Bauer, E. von Deimling, T.S. 2010 application/pdf text/plain; charset=utf-8 https://doi.org/10.34657/4080 https://oa.tib.eu/renate/handle/123456789/5451 eng eng Berlin : Springer Verlag CC BY-NC 2.0 Unported https://creativecommons.org/licenses/by-nc/2.0/ CC-BY-NC Climate Dynamics 34 (2010), Nr. 5 8.2 ka event Bayesian analysis Ocean diffusivity Paleo data Uncertainty diffusivity hydrogeochemistry ice core numerical model stochasticity uncertainty analysis Arctic Greenland 550 article Text 2010 ftleibnizopen https://doi.org/10.34657/4080 2023-03-06T00:23:18Z Greenland ice-core data containing the 8.2 ka event are utilized by a model-data intercomparison within the Earth system model of intermediate complexity, CLIMBER-2.3 to investigate their potential for constraining the range of uncertain ocean diffusivity properties. Within a stochastic version of the model (Bauer et al. in Paleoceanography 19:PA3014, 2004) it has been possible to mimic the pronounced cooling of the 8.2 ka event with relatively good accuracy considering the timing of the event in comparison to other modelling exercises. When statistically inferring from the 8.2 ka event on diffusivity the technical difficulty arises to establish the related likelihood numerically per realisation of the uncertain model parameters: while mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study the Bayesian Analysis leads to a sharp single-mode likelihood for ocean diffusivity parameters within CLIMBER-2.3. Depending on the prior distribution this likelihood leads to a reduction of uncertainty in ocean diffusivity parameters (e. g. for flat prior uncertainty in the vertical ocean diffusivity parameter is reduced by factor 2). These results highlight the potential of paleo data to constrain uncertain system properties and strongly suggest to make further steps with more complex models and richer data sets to harvest this potential. © The Author(s) 2009. publishedVersion Article in Journal/Newspaper Arctic Greenland Greenland ice core ice core LeibnizOpen (The Leibniz Association) Arctic Greenland |
institution |
Open Polar |
collection |
LeibnizOpen (The Leibniz Association) |
op_collection_id |
ftleibnizopen |
language |
English |
topic |
8.2 ka event Bayesian analysis Ocean diffusivity Paleo data Uncertainty diffusivity hydrogeochemistry ice core numerical model stochasticity uncertainty analysis Arctic Greenland 550 |
spellingShingle |
8.2 ka event Bayesian analysis Ocean diffusivity Paleo data Uncertainty diffusivity hydrogeochemistry ice core numerical model stochasticity uncertainty analysis Arctic Greenland 550 Lorenz, A. Held, H. Bauer, E. von Deimling, T.S. Constraining ocean diffusivity from the 8.2 ka event |
topic_facet |
8.2 ka event Bayesian analysis Ocean diffusivity Paleo data Uncertainty diffusivity hydrogeochemistry ice core numerical model stochasticity uncertainty analysis Arctic Greenland 550 |
description |
Greenland ice-core data containing the 8.2 ka event are utilized by a model-data intercomparison within the Earth system model of intermediate complexity, CLIMBER-2.3 to investigate their potential for constraining the range of uncertain ocean diffusivity properties. Within a stochastic version of the model (Bauer et al. in Paleoceanography 19:PA3014, 2004) it has been possible to mimic the pronounced cooling of the 8.2 ka event with relatively good accuracy considering the timing of the event in comparison to other modelling exercises. When statistically inferring from the 8.2 ka event on diffusivity the technical difficulty arises to establish the related likelihood numerically per realisation of the uncertain model parameters: while mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study the Bayesian Analysis leads to a sharp single-mode likelihood for ocean diffusivity parameters within CLIMBER-2.3. Depending on the prior distribution this likelihood leads to a reduction of uncertainty in ocean diffusivity parameters (e. g. for flat prior uncertainty in the vertical ocean diffusivity parameter is reduced by factor 2). These results highlight the potential of paleo data to constrain uncertain system properties and strongly suggest to make further steps with more complex models and richer data sets to harvest this potential. © The Author(s) 2009. publishedVersion |
format |
Article in Journal/Newspaper |
author |
Lorenz, A. Held, H. Bauer, E. von Deimling, T.S. |
author_facet |
Lorenz, A. Held, H. Bauer, E. von Deimling, T.S. |
author_sort |
Lorenz, A. |
title |
Constraining ocean diffusivity from the 8.2 ka event |
title_short |
Constraining ocean diffusivity from the 8.2 ka event |
title_full |
Constraining ocean diffusivity from the 8.2 ka event |
title_fullStr |
Constraining ocean diffusivity from the 8.2 ka event |
title_full_unstemmed |
Constraining ocean diffusivity from the 8.2 ka event |
title_sort |
constraining ocean diffusivity from the 8.2 ka event |
publisher |
Berlin : Springer Verlag |
publishDate |
2010 |
url |
https://doi.org/10.34657/4080 https://oa.tib.eu/renate/handle/123456789/5451 |
geographic |
Arctic Greenland |
geographic_facet |
Arctic Greenland |
genre |
Arctic Greenland Greenland ice core ice core |
genre_facet |
Arctic Greenland Greenland ice core ice core |
op_source |
Climate Dynamics 34 (2010), Nr. 5 |
op_rights |
CC BY-NC 2.0 Unported https://creativecommons.org/licenses/by-nc/2.0/ |
op_rightsnorm |
CC-BY-NC |
op_doi |
https://doi.org/10.34657/4080 |
_version_ |
1766342053797560320 |