Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data
This study investigates the long-term temporal patterns of sea level changes by analyzing monthly tide gauge data from 1950 to 2022 (42 to 72 years) along the European coastline and monthly altimetry data from 1992 to 2024 in the surrounding European seas. The primary focus is on signals with period...
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ftunivalicante:oai:rua.ua.es:10045/146227 2024-09-15T18:23:27+00:00 Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data Zid, Ferdous Vigo, Isabel Vargas-Alemañy, Juan A. Garcia-Garcia, David Universidad de Alicante. Departamento de Matemática Aplicada Geodesia por Satélites para la Observación de la Tierra y el Cambio Climático / Satellite Geodesy for Earth Observation and Climate Studies (SG) 2024-08-09 http://hdl.handle.net/10045/146227 https://doi.org/10.3390/rs16162931 eng eng MDPI https://doi.org/10.3390/rs16162931 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122142OB-I00 Remote Sensing. 2024, 16(16): 2931. https://doi.org/10.3390/rs16162931 2072-4292 http://hdl.handle.net/10045/146227 doi:10.3390/rs16162931 © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). info:eu-repo/semantics/openAccess Sea level Long-term variability Altimetry data Tide gauge data NAO AMO info:eu-repo/semantics/article 2024 ftunivalicante https://doi.org/10.3390/rs16162931 2024-09-03T23:46:33Z This study investigates the long-term temporal patterns of sea level changes by analyzing monthly tide gauge data from 1950 to 2022 (42 to 72 years) along the European coastline and monthly altimetry data from 1992 to 2024 in the surrounding European seas. The primary focus is on signals with periods longer than 5 years. The application of wavelet-based approaches and multiresolution analysis has enabled the isolation of signals with periods of approximately 8 and 16 years. However, the latter has only been observed in tide gauge data, as the altimetry time series is not sufficiently long. The same analysis was applied to the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO) indices, which enabled the detection of the same signals. The reported multiyear signals of sea level are correlated with NAO and AMO indices, particularly during the period spanning from 1975 to 2010. This research is supported by grant PID2021-122142OB-I00 funded by MCIN/AEI/10.13039/501100011033, grant PROMETEO/2021/030 funded by Generalitat Valenciana, and grant GVA-THINKINAZUL/2021/035 funded by Generalitat Valenciana and “European Union NextGenerationEU/PRTR”. Article in Journal/Newspaper North Atlantic North Atlantic oscillation RUA - Repositorio Institucional de la Universidad de Alicante Remote Sensing 16 16 2931 |
institution |
Open Polar |
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RUA - Repositorio Institucional de la Universidad de Alicante |
op_collection_id |
ftunivalicante |
language |
English |
topic |
Sea level Long-term variability Altimetry data Tide gauge data NAO AMO |
spellingShingle |
Sea level Long-term variability Altimetry data Tide gauge data NAO AMO Zid, Ferdous Vigo, Isabel Vargas-Alemañy, Juan A. Garcia-Garcia, David Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data |
topic_facet |
Sea level Long-term variability Altimetry data Tide gauge data NAO AMO |
description |
This study investigates the long-term temporal patterns of sea level changes by analyzing monthly tide gauge data from 1950 to 2022 (42 to 72 years) along the European coastline and monthly altimetry data from 1992 to 2024 in the surrounding European seas. The primary focus is on signals with periods longer than 5 years. The application of wavelet-based approaches and multiresolution analysis has enabled the isolation of signals with periods of approximately 8 and 16 years. However, the latter has only been observed in tide gauge data, as the altimetry time series is not sufficiently long. The same analysis was applied to the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO) indices, which enabled the detection of the same signals. The reported multiyear signals of sea level are correlated with NAO and AMO indices, particularly during the period spanning from 1975 to 2010. This research is supported by grant PID2021-122142OB-I00 funded by MCIN/AEI/10.13039/501100011033, grant PROMETEO/2021/030 funded by Generalitat Valenciana, and grant GVA-THINKINAZUL/2021/035 funded by Generalitat Valenciana and “European Union NextGenerationEU/PRTR”. |
author2 |
Universidad de Alicante. Departamento de Matemática Aplicada Geodesia por Satélites para la Observación de la Tierra y el Cambio Climático / Satellite Geodesy for Earth Observation and Climate Studies (SG) |
format |
Article in Journal/Newspaper |
author |
Zid, Ferdous Vigo, Isabel Vargas-Alemañy, Juan A. Garcia-Garcia, David |
author_facet |
Zid, Ferdous Vigo, Isabel Vargas-Alemañy, Juan A. Garcia-Garcia, David |
author_sort |
Zid, Ferdous |
title |
Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data |
title_short |
Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data |
title_full |
Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data |
title_fullStr |
Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data |
title_full_unstemmed |
Long-Term Sea Level Periodicities over the European Seas from Altimetry and Tide Gauge Data |
title_sort |
long-term sea level periodicities over the european seas from altimetry and tide gauge data |
publisher |
MDPI |
publishDate |
2024 |
url |
http://hdl.handle.net/10045/146227 https://doi.org/10.3390/rs16162931 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
https://doi.org/10.3390/rs16162931 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122142OB-I00 Remote Sensing. 2024, 16(16): 2931. https://doi.org/10.3390/rs16162931 2072-4292 http://hdl.handle.net/10045/146227 doi:10.3390/rs16162931 |
op_rights |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/rs16162931 |
container_title |
Remote Sensing |
container_volume |
16 |
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16 |
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2931 |
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1810463676390440960 |