RELATION OF SEA LEVEL ANOMALY AND TELECONNECTION PATTERN IN SOUTHEAST ASIA
The rising sea level poses a serious threat to Southeast Asia, endangering low-lying islands and coastal areas. Climate events like El Niño significantly influence the sea level changes and variability. However, Southeast Asia has a series of complex island structures located between the Indian and...
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Veröffentlicht in: | JOURNAL OF JSCE 2024, Vol.12(2), pp.24-17268 |
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Zusammenfassung: | The rising sea level poses a serious threat to Southeast Asia, endangering low-lying islands and coastal areas. Climate events like El Niño significantly influence the sea level changes and variability. However, Southeast Asia has a series of complex island structures located between the Indian and Pacific oceans, creating unique characteristics of Sea Level Anomaly (SLA) yet complex correlation with these climate events. This study investigates the possible teleconnection pattern of climate variability modes on SLA. A gridded SLA dataset derived from satellite altimetry (CMEMS) for 1993-2022 was utilized. Eleven potential climate indices to represent the Pacific and Indian Oceans were analyzed. While ENSO primarily influences the Pacific Ocean, the best index to capture ENSO impact depends on the region and the variable studied. Hence, four ENSO-related climate indices (Niño 3.4, ONI, MEI, and SOI) were included to identify the most appropriate index to describe SLA relation to ENSO in Southeast Asia. ONI was subsequently excluded due to its high correlation with Niño 3.4 (R = 0.99). Initially, the correlation coefficient of each index and SLA were calculated. Six indices exhibited high correlation, indicated by statistically significant areas exceeding 50% at a 95% confidence level. Multiple regression analysis was then conducted along with Relative Weight Analysis (RWA) to identify every index's contribution (importance) level. PWP emerged as the most important index, with a significant area of 95.24% and a contribution level of 35.60%. MEI was also identified as the best ENSO index with the highest contribution level. Furthermore, this study explored the long-term spatiotemporal variability of SLA. On the interdecadal scale, SLA in Southeast Asia is increasing from one interdecadal to another with a decreasing speed (trend). The anomaly is higher and more fluctuative during DJF. Moreover, variability is higher in the open ocean compared to the semi-enclosed ocean. |
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ISSN: | 2187-5103 2187-5103 |
DOI: | 10.2208/journalofjsce.24-17268 |