Pattern recognition of ocean pH
The manuscript shows how the few, scattered, latest measurements of ocean pH lacking a proper spatial and time coverage do not permit a meaningful computation of global trends, as the ocean pH is strongly variable in latitude, longitude and depth and very likely is subject to the multi-decadal oscil...
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| Format: | Article |
| Language: | English |
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De Gruyter
2016-09-01
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| Series: | Nonlinear Engineering |
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| Online Access: | https://doi.org/10.1515/nleng-2016-0005 |
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Article |
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doaj-c3abb77095104729a61cb426c7caad192021-09-06T19:21:06ZengDe GruyterNonlinear Engineering2192-80102192-80292016-09-015320521710.1515/nleng-2016-0005Pattern recognition of ocean pHParker AlbertThe manuscript shows how the few, scattered, latest measurements of ocean pH lacking a proper spatial and time coverage do not permit a meaningful computation of global trends, as the ocean pH is strongly variable in latitude, longitude and depth and very likely is subject to the multi-decadal oscillations that have been identified in the atmospheric and ocean systems. The proposed mathematical model is based on the assumption that the monthly averaged ocean pH may be described by the superposition of a linear trend and inter-annual, decadal and multi-decadal oscillations, with linear and sinusoidal regression coefficients requiring data that are presently unavailable.https://doi.org/10.1515/nleng-2016-0005ocean phacidityclimate modelsmeasurementssimulations |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Parker Albert |
| spellingShingle |
Parker Albert Pattern recognition of ocean pH Nonlinear Engineering ocean ph acidity climate models measurements simulations |
| author_facet |
Parker Albert |
| author_sort |
Parker Albert |
| title |
Pattern recognition of ocean pH |
| title_short |
Pattern recognition of ocean pH |
| title_full |
Pattern recognition of ocean pH |
| title_fullStr |
Pattern recognition of ocean pH |
| title_full_unstemmed |
Pattern recognition of ocean pH |
| title_sort |
pattern recognition of ocean ph |
| publisher |
De Gruyter |
| series |
Nonlinear Engineering |
| issn |
2192-8010 2192-8029 |
| publishDate |
2016-09-01 |
| description |
The manuscript shows how the few, scattered, latest measurements of ocean pH lacking a proper spatial and time coverage do not permit a meaningful computation of global trends, as the ocean pH is strongly variable in latitude, longitude and depth and very likely is subject to the multi-decadal oscillations that have been identified in the atmospheric and ocean systems. The proposed mathematical model is based on the assumption that the monthly averaged ocean pH may be described by the superposition of a linear trend and inter-annual, decadal and multi-decadal oscillations, with linear and sinusoidal regression coefficients requiring data that are presently unavailable. |
| topic |
ocean ph acidity climate models measurements simulations |
| url |
https://doi.org/10.1515/nleng-2016-0005 |
| work_keys_str_mv |
AT parkeralbert patternrecognitionofoceanph |
| _version_ |
1717775205824200704 |