Interglacial climate dynamics and advanced time series analysis

Studying the climate dynamics of past interglacials (IGs) helps to better assess the anthropogenically influenced dynamics of the current IG, the Holocene. We select the IG portions from the EPICA Dome C ice core archive, which covers the past 800 ka, to apply methods of statistical time series anal...

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Main Authors: Mudelsee, Manfred, Bermejo, M., Köhler, Peter, Lohmann, Gerrit
Format: Conference Object
Language:unknown
Published: 2013
Subjects:
Online Access:https://epic.awi.de/id/eprint/32607/
https://epic.awi.de/id/eprint/32607/1/EGU2013-3313-1.pdf
https://hdl.handle.net/10013/epic.41184
https://hdl.handle.net/10013/epic.41184.d001
id ftawi:oai:epic.awi.de:32607
record_format openpolar
spelling ftawi:oai:epic.awi.de:32607 2023-05-15T16:06:18+02:00 Interglacial climate dynamics and advanced time series analysis Mudelsee, Manfred Bermejo, M. Köhler, Peter Lohmann, Gerrit 2013-04-08 application/pdf https://epic.awi.de/id/eprint/32607/ https://epic.awi.de/id/eprint/32607/1/EGU2013-3313-1.pdf https://hdl.handle.net/10013/epic.41184 https://hdl.handle.net/10013/epic.41184.d001 unknown https://epic.awi.de/id/eprint/32607/1/EGU2013-3313-1.pdf https://hdl.handle.net/10013/epic.41184.d001 Mudelsee, M. orcid:0000-0002-2364-9561 , Bermejo, M. , Köhler, P. orcid:0000-0003-0904-8484 and Lohmann, G. orcid:0000-0003-2089-733X (2013) Interglacial climate dynamics and advanced time series analysis , EGU General Assembly, Vienna, Austria, 7 April 2013 - 12 April 2013 . hdl:10013/epic.41184 EPIC3EGU General Assembly, Vienna, Austria, 2013-04-07-2013-04-12 Conference notRev 2013 ftawi 2021-12-24T15:38:28Z Studying the climate dynamics of past interglacials (IGs) helps to better assess the anthropogenically influenced dynamics of the current IG, the Holocene. We select the IG portions from the EPICA Dome C ice core archive, which covers the past 800 ka, to apply methods of statistical time series analysis (Mudelsee 2010). The analysed variables are deuterium/H (indicating temperature) (Jouzel et al. 2007), greenhouse gases (Siegenthaler et al. 2005, Loulergue et al. 2008, Lü ̈thi et al. 2008) and a model-co-derived climate radiative forcing (Köhler et al. 2010). We select additionally high-resolution sea-surface-temperature records from the marine sedimentary archive. The first statistical method, persistence time estimation (Mudelsee 2002) lets us infer the ’climate memory’ property of IGs. Second, linear regression informs about long-term climate trends during IGs. Third, ramp function regression (Mudelsee 2000) is adapted to look on abrupt climate changes during IGs. We compare the Holocene with previous IGs in terms of these mathematical approaches, interprete results in a climate context, assess uncertainties and the requirements to data from old IGs for yielding results of ’acceptable’ accuracy. This work receives financial support from the Deutsche Forschungsgemeinschaft (Project ClimSens within the DFG Research Priority Program INTERDYNAMIK) and the European Commission (Marie Curie Initial Training Network LINC, No. 289447, within the 7th Framework Programme). Conference Object EPICA ice core Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
institution Open Polar
collection Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
op_collection_id ftawi
language unknown
description Studying the climate dynamics of past interglacials (IGs) helps to better assess the anthropogenically influenced dynamics of the current IG, the Holocene. We select the IG portions from the EPICA Dome C ice core archive, which covers the past 800 ka, to apply methods of statistical time series analysis (Mudelsee 2010). The analysed variables are deuterium/H (indicating temperature) (Jouzel et al. 2007), greenhouse gases (Siegenthaler et al. 2005, Loulergue et al. 2008, Lü ̈thi et al. 2008) and a model-co-derived climate radiative forcing (Köhler et al. 2010). We select additionally high-resolution sea-surface-temperature records from the marine sedimentary archive. The first statistical method, persistence time estimation (Mudelsee 2002) lets us infer the ’climate memory’ property of IGs. Second, linear regression informs about long-term climate trends during IGs. Third, ramp function regression (Mudelsee 2000) is adapted to look on abrupt climate changes during IGs. We compare the Holocene with previous IGs in terms of these mathematical approaches, interprete results in a climate context, assess uncertainties and the requirements to data from old IGs for yielding results of ’acceptable’ accuracy. This work receives financial support from the Deutsche Forschungsgemeinschaft (Project ClimSens within the DFG Research Priority Program INTERDYNAMIK) and the European Commission (Marie Curie Initial Training Network LINC, No. 289447, within the 7th Framework Programme).
format Conference Object
author Mudelsee, Manfred
Bermejo, M.
Köhler, Peter
Lohmann, Gerrit
spellingShingle Mudelsee, Manfred
Bermejo, M.
Köhler, Peter
Lohmann, Gerrit
Interglacial climate dynamics and advanced time series analysis
author_facet Mudelsee, Manfred
Bermejo, M.
Köhler, Peter
Lohmann, Gerrit
author_sort Mudelsee, Manfred
title Interglacial climate dynamics and advanced time series analysis
title_short Interglacial climate dynamics and advanced time series analysis
title_full Interglacial climate dynamics and advanced time series analysis
title_fullStr Interglacial climate dynamics and advanced time series analysis
title_full_unstemmed Interglacial climate dynamics and advanced time series analysis
title_sort interglacial climate dynamics and advanced time series analysis
publishDate 2013
url https://epic.awi.de/id/eprint/32607/
https://epic.awi.de/id/eprint/32607/1/EGU2013-3313-1.pdf
https://hdl.handle.net/10013/epic.41184
https://hdl.handle.net/10013/epic.41184.d001
genre EPICA
ice core
genre_facet EPICA
ice core
op_source EPIC3EGU General Assembly, Vienna, Austria, 2013-04-07-2013-04-12
op_relation https://epic.awi.de/id/eprint/32607/1/EGU2013-3313-1.pdf
https://hdl.handle.net/10013/epic.41184.d001
Mudelsee, M. orcid:0000-0002-2364-9561 , Bermejo, M. , Köhler, P. orcid:0000-0003-0904-8484 and Lohmann, G. orcid:0000-0003-2089-733X (2013) Interglacial climate dynamics and advanced time series analysis , EGU General Assembly, Vienna, Austria, 7 April 2013 - 12 April 2013 . hdl:10013/epic.41184
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