Sea Level Variability in the Red Sea: A Persistent East–West Pattern
Based on 26 years of satellite altimetry, this study reveals the presence of a persistent east–west pattern in the sea level of the Red Sea, which is visible throughout the years when considering the east–west difference in sea level. This eastern–western (EW) difference is positive during winter wh...
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ftmdpi:oai:mdpi.com:/2072-4292/12/13/2090/ 2023-08-20T04:08:18+02:00 Sea Level Variability in the Red Sea: A Persistent East–West Pattern Cheriyeri Abdulla Abdullah Al-Subhi 2020-06-30 application/pdf https://doi.org/10.3390/rs12132090 EN eng Multidisciplinary Digital Publishing Institute Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs12132090 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 13; Pages: 2090 satellite altimetry sea level anomaly El-Nino Southern Oscillation Indian Ocean Dipole North Atlantic Oscillation Red Sea Text 2020 ftmdpi https://doi.org/10.3390/rs12132090 2023-07-31T23:42:35Z Based on 26 years of satellite altimetry, this study reveals the presence of a persistent east–west pattern in the sea level of the Red Sea, which is visible throughout the years when considering the east–west difference in sea level. This eastern–western (EW) difference is positive during winter when a higher sea level is observed at the eastern coast of the Red Sea and the opposite occurs during summer. May and October are transition months that show a mixed pattern in the sea level difference. The EW difference in the southern Red Sea has a slightly higher range compared to that of the northern region during summer, by an average of 0.2 cm. Wavelet analysis shows a significant annual cycle along with other signals of lower magnitude for both the northern and southern Red Sea. Removing the annual cycle reveals two energy peaks with periodicities of <12 months and 3–7 years, representing the intraseasonal and El Nino—Southern Oscillation (ENSO) signals, respectively. Empirical Orthogonal Function (EOF) analysis shows that EOF1 corresponds to 98% of total variability, EOF2 to 1.3%, and EOF3 to 0.4%. The remote response of ENSO is evident in the variability in the atmospheric bridge, while that of the Indian Ocean Dipole (IOD) and North Atlantic Oscillation (NAO) is weak. Three physical mechanisms are responsible for the occurrence of this EW difference phenomenon, namely wind, buoyancy, and the polarity of eddies. Text North Atlantic North Atlantic oscillation MDPI Open Access Publishing Indian Remote Sensing 12 13 2090 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
satellite altimetry sea level anomaly El-Nino Southern Oscillation Indian Ocean Dipole North Atlantic Oscillation Red Sea |
spellingShingle |
satellite altimetry sea level anomaly El-Nino Southern Oscillation Indian Ocean Dipole North Atlantic Oscillation Red Sea Cheriyeri Abdulla Abdullah Al-Subhi Sea Level Variability in the Red Sea: A Persistent East–West Pattern |
topic_facet |
satellite altimetry sea level anomaly El-Nino Southern Oscillation Indian Ocean Dipole North Atlantic Oscillation Red Sea |
description |
Based on 26 years of satellite altimetry, this study reveals the presence of a persistent east–west pattern in the sea level of the Red Sea, which is visible throughout the years when considering the east–west difference in sea level. This eastern–western (EW) difference is positive during winter when a higher sea level is observed at the eastern coast of the Red Sea and the opposite occurs during summer. May and October are transition months that show a mixed pattern in the sea level difference. The EW difference in the southern Red Sea has a slightly higher range compared to that of the northern region during summer, by an average of 0.2 cm. Wavelet analysis shows a significant annual cycle along with other signals of lower magnitude for both the northern and southern Red Sea. Removing the annual cycle reveals two energy peaks with periodicities of <12 months and 3–7 years, representing the intraseasonal and El Nino—Southern Oscillation (ENSO) signals, respectively. Empirical Orthogonal Function (EOF) analysis shows that EOF1 corresponds to 98% of total variability, EOF2 to 1.3%, and EOF3 to 0.4%. The remote response of ENSO is evident in the variability in the atmospheric bridge, while that of the Indian Ocean Dipole (IOD) and North Atlantic Oscillation (NAO) is weak. Three physical mechanisms are responsible for the occurrence of this EW difference phenomenon, namely wind, buoyancy, and the polarity of eddies. |
format |
Text |
author |
Cheriyeri Abdulla Abdullah Al-Subhi |
author_facet |
Cheriyeri Abdulla Abdullah Al-Subhi |
author_sort |
Cheriyeri Abdulla |
title |
Sea Level Variability in the Red Sea: A Persistent East–West Pattern |
title_short |
Sea Level Variability in the Red Sea: A Persistent East–West Pattern |
title_full |
Sea Level Variability in the Red Sea: A Persistent East–West Pattern |
title_fullStr |
Sea Level Variability in the Red Sea: A Persistent East–West Pattern |
title_full_unstemmed |
Sea Level Variability in the Red Sea: A Persistent East–West Pattern |
title_sort |
sea level variability in the red sea: a persistent east–west pattern |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12132090 |
geographic |
Indian |
geographic_facet |
Indian |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Remote Sensing; Volume 12; Issue 13; Pages: 2090 |
op_relation |
Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs12132090 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs12132090 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
13 |
container_start_page |
2090 |
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1774720498518720512 |