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Cross-Wavelet Analysis: a Tool for Detection of Relationships between Paleoclimate Proxy Records
Cross-wavelet transform (XWT) is proposed as a data analysis technique for geological time-series. XWT permits the detection of cross-magnitude, phase differences (= lag time), nonstationarity, and coherency between signals from different paleoclimate records that may exhibit large stratigraphic unc...
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| Published in: | Mathematical geosciences 2008-07, Vol.40 (5), p.575-586 |
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| Main Authors: | , |
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| Language: | English |
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| cites | cdi_FETCH-LOGICAL-a369t-940834a496b3d9b9961614ad65cad610f9f06dbbcbd9663ca979a29a836956863 |
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| container_title | Mathematical geosciences |
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| creator | Prokoph, Andreas El Bilali, Hafida |
| description | Cross-wavelet transform (XWT) is proposed as a data analysis technique for geological time-series. XWT permits the detection of cross-magnitude, phase differences (= lag time), nonstationarity, and coherency between signals from different paleoclimate records that may exhibit large stratigraphic uncertainties and noise levels. The approach presented herein utilizes a continuous XWT technique with Morlet wavelet as the mother function, allows for variable scaling factors for time and scale sampling, and the automatic extraction of the most significant periodic signals. XWT and cross-spectral analysis is applied on computer generated time-series as well as two independently sampled proxy records (CO
2
content approximated from plant cuticles and paleotemperature derived from
δ
18
O from marine fossil carbonate) of the last 290 Ma. The influence of nonstationarities in the paleoclimate records that are introduced by stratigraphic uncertainties were a particular focus of this study. The XWT outputs of the computer-models indicate that a potential causal relationship can be distorted if different geological time-scale and/or large stratigraphic uncertainties have been used. XWT detect strong cross-amplitudes (∼200 ppm ‰) between the CO
2
and
δ
18
O record in the 20–50 Myr waveband, however, fluctuating phase differences prevent a statistical conclusion on causal relationship at this waveband. |
| doi_str_mv | 10.1007/s11004-008-9170-8 |
| format | article |
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2
content approximated from plant cuticles and paleotemperature derived from
δ
18
O from marine fossil carbonate) of the last 290 Ma. The influence of nonstationarities in the paleoclimate records that are introduced by stratigraphic uncertainties were a particular focus of this study. The XWT outputs of the computer-models indicate that a potential causal relationship can be distorted if different geological time-scale and/or large stratigraphic uncertainties have been used. XWT detect strong cross-amplitudes (∼200 ppm ‰) between the CO
2
and
δ
18
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2
content approximated from plant cuticles and paleotemperature derived from
δ
18
O from marine fossil carbonate) of the last 290 Ma. The influence of nonstationarities in the paleoclimate records that are introduced by stratigraphic uncertainties were a particular focus of this study. The XWT outputs of the computer-models indicate that a potential causal relationship can be distorted if different geological time-scale and/or large stratigraphic uncertainties have been used. XWT detect strong cross-amplitudes (∼200 ppm ‰) between the CO
2
and
δ
18
O record in the 20–50 Myr waveband, however, fluctuating phase differences prevent a statistical conclusion on causal relationship at this waveband.</description><subject>Carbon dioxide</subject><subject>Chemistry and Earth Sciences</subject><subject>Computer Science</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Fossils</subject><subject>Geological time</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Hydrogeology</subject><subject>Noise levels</subject><subject>Paleoclimate</subject><subject>Paleontology</subject><subject>Physics</subject><subject>Special Issue</subject><subject>Spectral analysis</subject><subject>Statistics for Engineering</subject><subject>Stratigraphy</subject><subject>Time series</subject><subject>Wavelet transforms</subject><issn>1874-8961</issn><issn>1874-8953</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><recordid>eNp1kM9KAzEQxoMoWKsP4C148BZNNrtp4q3Uv1CwlIrHkN2d1S3ppiZbtW_js_hkZllRELzMNwPfN8z8EDpm9IxROjoPLEpKKJVEsRElcgcNmBylRKqM7_70gu2jgxCWlArGMzZAZuJdCOTRvIKFFo8bY7ehDhfY4IVzFlfO40tooWhr12BXfX7MwZpuCM_1OuAc2jeABs-MBVfYemVawDPv3rd4DoXzZThEe5WxAY6-dYgerq8Wk1syvb-5m4ynxHChWqJSKnlqUiVyXqpcxVMFS00psiIWRitVUVHmeZGXSgheGDVSJlFGxnQmpOBDdNrvXXv3soHQ6lUdCrDWNOA2QfNEJiyTKhpP_hiXbuPj40EnlCdplkYZItabio6Ph0qvfXzObzWjuiOue-I6EtcdcS1jJukzIXqbJ_C_i_8PfQHbb4QV</recordid><startdate>20080701</startdate><enddate>20080701</enddate><creator>Prokoph, Andreas</creator><creator>El Bilali, Hafida</creator><general>Springer-Verlag</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope></search><sort><creationdate>20080701</creationdate><title>Cross-Wavelet Analysis: a Tool for Detection of Relationships between Paleoclimate Proxy Records</title><author>Prokoph, Andreas ; El Bilali, Hafida</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a369t-940834a496b3d9b9961614ad65cad610f9f06dbbcbd9663ca979a29a836956863</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Carbon dioxide</topic><topic>Chemistry and Earth Sciences</topic><topic>Computer Science</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Fossils</topic><topic>Geological time</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Hydrogeology</topic><topic>Noise levels</topic><topic>Paleoclimate</topic><topic>Paleontology</topic><topic>Physics</topic><topic>Special Issue</topic><topic>Spectral analysis</topic><topic>Statistics for Engineering</topic><topic>Stratigraphy</topic><topic>Time series</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Prokoph, Andreas</creatorcontrib><creatorcontrib>El Bilali, Hafida</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - 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2
content approximated from plant cuticles and paleotemperature derived from
δ
18
O from marine fossil carbonate) of the last 290 Ma. The influence of nonstationarities in the paleoclimate records that are introduced by stratigraphic uncertainties were a particular focus of this study. The XWT outputs of the computer-models indicate that a potential causal relationship can be distorted if different geological time-scale and/or large stratigraphic uncertainties have been used. XWT detect strong cross-amplitudes (∼200 ppm ‰) between the CO
2
and
δ
18
O record in the 20–50 Myr waveband, however, fluctuating phase differences prevent a statistical conclusion on causal relationship at this waveband.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s11004-008-9170-8</doi><tpages>12</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1874-8961 |
| ispartof | Mathematical geosciences, 2008-07, Vol.40 (5), p.575-586 |
| issn | 1874-8961 1874-8953 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_32821589 |
| source | Springer Nature |
| subjects | Carbon dioxide Chemistry and Earth Sciences Computer Science Earth and Environmental Science Earth Sciences Fossils Geological time Geotechnical Engineering & Applied Earth Sciences Hydrogeology Noise levels Paleoclimate Paleontology Physics Special Issue Spectral analysis Statistics for Engineering Stratigraphy Time series Wavelet transforms |
| title | Cross-Wavelet Analysis: a Tool for Detection of Relationships between Paleoclimate Proxy Records |
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