Automated ice-core layer-counting with strong univariate signals
We present an automated process for determining the annual layer chronology of an ice-core with a strong annual signal, utilising the hydrogen peroxide record from an Antarctic Peninsula ice-core as a test signal on which to count annual cycles and explain the Methods. The signal is de-trended and n...
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ftanucanberra:oai:digitalcollections.anu.edu.au:1885/69420 2023-05-15T13:36:32+02:00 Automated ice-core layer-counting with strong univariate signals Wheatley, J.J. Blackwell, P.G. Abram, Nerilie McConnell, J.R. Thomas, E.R. Wolff, E.W. 2015-12-10T23:34:24Z http://hdl.handle.net/1885/69420 unknown Copernicus GmbH 1814-9324 http://hdl.handle.net/1885/69420 Climate of the Past Journal article 2015 ftanucanberra 2015-12-28T23:34:29Z We present an automated process for determining the annual layer chronology of an ice-core with a strong annual signal, utilising the hydrogen peroxide record from an Antarctic Peninsula ice-core as a test signal on which to count annual cycles and explain the Methods. The signal is de-trended and normalised before being split into sections with a deterministic cycle count and those that need more attention. Possible reconstructions for the uncertain sections are determined which could be used as a visual aid for manual counting, and a simple method for assigning probability measures to each reconstruction is discussed. The robustness of this process is explored by applying it to versions of two different chemistry signals from the same stretch of the NGRIP (North Greenland Ice Core Project) ice-core, which shows more variation in annual layer thickness, with and without thinning to mimic poorer quality data. An adapted version of these Methods is applied to the more challenging non-sea-salt sulphur signal from the same Antarctic Peninsula core from which the hydrogen peroxide signal was taken. These Methods could readily be adapted for use on much longer datasets, thereby reducing manual effort and providing a robust automated layer-counting methodology. Article in Journal/Newspaper Antarc* Antarctic Antarctic Peninsula Greenland Greenland ice core Greenland Ice core Project ice core NGRIP North Greenland North Greenland Ice Core Project Australian National University: ANU Digital Collections Antarctic Antarctic Peninsula Greenland |
institution |
Open Polar |
collection |
Australian National University: ANU Digital Collections |
op_collection_id |
ftanucanberra |
language |
unknown |
description |
We present an automated process for determining the annual layer chronology of an ice-core with a strong annual signal, utilising the hydrogen peroxide record from an Antarctic Peninsula ice-core as a test signal on which to count annual cycles and explain the Methods. The signal is de-trended and normalised before being split into sections with a deterministic cycle count and those that need more attention. Possible reconstructions for the uncertain sections are determined which could be used as a visual aid for manual counting, and a simple method for assigning probability measures to each reconstruction is discussed. The robustness of this process is explored by applying it to versions of two different chemistry signals from the same stretch of the NGRIP (North Greenland Ice Core Project) ice-core, which shows more variation in annual layer thickness, with and without thinning to mimic poorer quality data. An adapted version of these Methods is applied to the more challenging non-sea-salt sulphur signal from the same Antarctic Peninsula core from which the hydrogen peroxide signal was taken. These Methods could readily be adapted for use on much longer datasets, thereby reducing manual effort and providing a robust automated layer-counting methodology. |
format |
Article in Journal/Newspaper |
author |
Wheatley, J.J. Blackwell, P.G. Abram, Nerilie McConnell, J.R. Thomas, E.R. Wolff, E.W. |
spellingShingle |
Wheatley, J.J. Blackwell, P.G. Abram, Nerilie McConnell, J.R. Thomas, E.R. Wolff, E.W. Automated ice-core layer-counting with strong univariate signals |
author_facet |
Wheatley, J.J. Blackwell, P.G. Abram, Nerilie McConnell, J.R. Thomas, E.R. Wolff, E.W. |
author_sort |
Wheatley, J.J. |
title |
Automated ice-core layer-counting with strong univariate signals |
title_short |
Automated ice-core layer-counting with strong univariate signals |
title_full |
Automated ice-core layer-counting with strong univariate signals |
title_fullStr |
Automated ice-core layer-counting with strong univariate signals |
title_full_unstemmed |
Automated ice-core layer-counting with strong univariate signals |
title_sort |
automated ice-core layer-counting with strong univariate signals |
publisher |
Copernicus GmbH |
publishDate |
2015 |
url |
http://hdl.handle.net/1885/69420 |
geographic |
Antarctic Antarctic Peninsula Greenland |
geographic_facet |
Antarctic Antarctic Peninsula Greenland |
genre |
Antarc* Antarctic Antarctic Peninsula Greenland Greenland ice core Greenland Ice core Project ice core NGRIP North Greenland North Greenland Ice Core Project |
genre_facet |
Antarc* Antarctic Antarctic Peninsula Greenland Greenland ice core Greenland Ice core Project ice core NGRIP North Greenland North Greenland Ice Core Project |
op_source |
Climate of the Past |
op_relation |
1814-9324 http://hdl.handle.net/1885/69420 |
_version_ |
1766080254811570176 |