Understanding the Effect of Internal Climate Variability on 20th Century Indian Ocean Sea Level: Results from Newly Reconstructed Sea Level Data

<p>Densely populated low-lying coastal zones of countries that border the Indian Ocean are at risk due to sea level rise. However, sea level change in the Indian Ocean is poorly understood primarily due to short and sparse tide gauge observations. Although satellite altimetry provides accurate basin-wide sea level measurements, trends computed from its relatively short (~27-year) data record are heavily influenced by interannual to multi-decadal variability. To accurately project future Indian Ocean sea level trends using altimeter data it is imperative that trends associated with fluctuating internal variability (interannual-decadal) be identified and extracted, which in turn requires long (~100-year) data. An improved representation of basin-wide pre-satellite sea level variability can be obtained from reconstructions and reanalysis. However, over the Indian Ocean inconsistencies have been identified across these products. In this research, a new multivariate sea level reconstruction framework was developed which uses sea level pressure and sea surface temperature to help supplement the lack of 20th century Indian Ocean tide gauge measurements. Basis functions computed over the Indian Ocean and generated using Cyclostationary Empirical Orthogonal Functions helped to better capture regional variability. Using this new century long dataset, the dominant mode of sea level variability over the tropical Indian Ocean was shown to be related to concurrent (Indian Ocean Dipole and El Nino Southern Oscillation) events. Concurrent events produce a strong sea level response and can drive spatial patterns opposite to that of the prevailing climatology. These events can persist for beyond 6-months thus, having important dynamical implications. A trend in sea level was also identified, which is likely related to the increase in occurrence of positive Indian Ocean Dipole events over the 20th century. By accurately identifying and removing the fraction related to internal variability, the component of sea level rise related to anthropogenic forcing can be isolated from the altimeter record. Collectively, these results seek to improve the understanding of how climate modes impact sea level over the Indian Ocean with the ultimate goal of helping adaptation and mitigation efforts in Indian Ocean rim countries facing the threat of sea level rise.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Ocean & Earth Sciences

Year dc:date.available

2021

Author dc:creator

• Kumar, Praveen

Contributors dc:contributor

• Tal Ezer
• Benjamin Hamlington
• John Klinck
• John A. Adam

• Indian Ocean
• interannual-to-decadal
• Multivariate reconstruction
• Sea level
• Climate
• Oceanography
• Remote Sensing

Statement dc:rights

• <p>In Copyright. URI: <a href="http://rightsstatements.org/vocab/InC/1.0/">http://rightsstatements.org/vocab/InC/1.0/</a> This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).</p>

Identifier

9798516058929

OAI identifier oai:identifier

oai:digitalcommons.odu.edu:oeas_etds-1178