Modelling the Interactions in Paleoclimate Data from Ice Cores
This paper considers methods for testing directions of causation in the paleoclimate series for temperature and CO2 concentration derived from Antarctic ice cores from 800,000 years BP. These series are well-known to move together in the transitions between glacial and interglacial periods, but the...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.364.6869 2023-05-15T14:05:28+02:00 Modelling the Interactions in Paleoclimate Data from Ice Cores James Davidson Alemtsehai Turasie The Pennsylvania State University CiteSeerX Archives 2013 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.6869 http://people.exeter.ac.uk/jehd201/paleoclimate.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.6869 http://people.exeter.ac.uk/jehd201/paleoclimate.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://people.exeter.ac.uk/jehd201/paleoclimate.pdf text 2013 ftciteseerx 2016-01-08T00:59:38Z This paper considers methods for testing directions of causation in the paleoclimate series for temperature and CO2 concentration derived from Antarctic ice cores from 800,000 years BP. These series are well-known to move together in the transitions between glacial and interglacial periods, but the dynamic relationship between the series is open to dispute. Bivariate models are constructed, in the context of which we perform tests for Granger causality, or in other words for asymmetry in the pattern of dynamic interactions. An important question is the stationarity of the series, because di¤erent statistical techniques are called for in stationary and integrated models. Previous work with climate data has focused on a cointegration approach appropriate to integrated series, but a range of tests show no evidence of integrated behaviour in these seres. A second important question is linearity, whether the dynamics in mean can be adequately represented by a high-order vector autoregressive process. This modelling approach is compared with a nonlinear Markov switching mechanism, in which the glacial/interglacial switches are controlled by a common hidden discrete process with …xed conditional probabilities of changes of state. A further characteristic of the data that comes to light is pronounced conditional heteroscedasticity, with much larger disturbances in evidence around the glacial/interglacial transitions.This data feature is e¤ectively accounted for by …tting a GARCH component. 1 Text Antarc* Antarctic Unknown Antarctic |
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This paper considers methods for testing directions of causation in the paleoclimate series for temperature and CO2 concentration derived from Antarctic ice cores from 800,000 years BP. These series are well-known to move together in the transitions between glacial and interglacial periods, but the dynamic relationship between the series is open to dispute. Bivariate models are constructed, in the context of which we perform tests for Granger causality, or in other words for asymmetry in the pattern of dynamic interactions. An important question is the stationarity of the series, because di¤erent statistical techniques are called for in stationary and integrated models. Previous work with climate data has focused on a cointegration approach appropriate to integrated series, but a range of tests show no evidence of integrated behaviour in these seres. A second important question is linearity, whether the dynamics in mean can be adequately represented by a high-order vector autoregressive process. This modelling approach is compared with a nonlinear Markov switching mechanism, in which the glacial/interglacial switches are controlled by a common hidden discrete process with …xed conditional probabilities of changes of state. A further characteristic of the data that comes to light is pronounced conditional heteroscedasticity, with much larger disturbances in evidence around the glacial/interglacial transitions.This data feature is e¤ectively accounted for by …tting a GARCH component. 1 |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
James Davidson Alemtsehai Turasie |
spellingShingle |
James Davidson Alemtsehai Turasie Modelling the Interactions in Paleoclimate Data from Ice Cores |
author_facet |
James Davidson Alemtsehai Turasie |
author_sort |
James Davidson |
title |
Modelling the Interactions in Paleoclimate Data from Ice Cores |
title_short |
Modelling the Interactions in Paleoclimate Data from Ice Cores |
title_full |
Modelling the Interactions in Paleoclimate Data from Ice Cores |
title_fullStr |
Modelling the Interactions in Paleoclimate Data from Ice Cores |
title_full_unstemmed |
Modelling the Interactions in Paleoclimate Data from Ice Cores |
title_sort |
modelling the interactions in paleoclimate data from ice cores |
publishDate |
2013 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.6869 http://people.exeter.ac.uk/jehd201/paleoclimate.pdf |
geographic |
Antarctic |
geographic_facet |
Antarctic |
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Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_source |
http://people.exeter.ac.uk/jehd201/paleoclimate.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.6869 http://people.exeter.ac.uk/jehd201/paleoclimate.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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