Rising sea levels pose a potential threat to the low-lying regions for the countries that surround the Indo-Pacific belt. Changes in sea level and its variability are intrinsically connected with sea surface temperature (SST) variations and associated wind field patterns in the Indo-Pacific Ocean (IPO). SST-based climate variability modes such as El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) tend to influence the sea level variability over the IPO significantly. The impact of climate variability modes on SLA, SST, and wind speed is examined by using regression analysis.The study considered two different datasets, namely the AVISO SLA and reconstructed SSHA from 1993 to 2019 and 1952 to 2009, respectively. SLA and SST both exhibit a decreasing trend from 1997 to 2007 year-round; however, by the next decade (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018), an overall increasing trend is evident in both parameters throughout the year. The influence of independent ENSO after removing the PDO signal (ENSOj PDO ) on SLA and SST exhibits statistically significant increases over the eastern PO, western tropical IO, but decreases over the AS, eastern IO, and western PO during DJF. SLA response to IOD removing ENSO (IODj ENSO ) during SON includes increases over western to central tropical IO, and decreases over the AS extending up to eastern IO. Lastly, for the PDO influence in DJF, statistically significant increases in SLA are evident over the north PO extending up to eastern PO; however, PDOj ENSO influence over SLA exhibits similar but significantly reduced amplitudes. Composite analysis of different phase combinations of PDO (IOD) with El Niño (La Niña) exhibits stronger (weaker) influences during DJF (SON) season.
In the Indo-Pacific Ocean (IPO), extreme significant wave heights (SWHs) can substantially induce coastal erosion, flooding, and devastating impacts on coastal livelihoods. This study examines the seasonal influence of the El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Southern Annular Mode (SAM), and Pacific North American (PNA) pattern on extreme windwave parameters. The climatic extremes are calculated utilizing ERA5 reanalysis datasets from 1979 to 2019 and a nonstationary generalized extreme value distribution. Significant increases in extreme wind-sea (Hmax) and swell SWH (Hmax Sw ) response to ENSO occur over the northeast North Pacific (NP) during December-February (DJF) and western NP during June-August (JJA).The PNA influence exhibits a similar pattern to ENSO during DJF yet is inactive in JJA. Hmax and Hmax Sw responses to the IOD during September-November (SON) include significant increases over the western Pacific, southern Indian Ocean (IO), and southwest tropical IO, yet decreases over the central tropical IO. The Hmax Sw response to the SAM is larger than that for Hmax over the southern IPO during DJF, which extends toward the eastern Pacific in March-May (MAM). Overall, extreme wind-sea and swell parameter responses are found to be associated with sea level pressure (SLP) and SLP gradients. K E Y W O R D S climate variability, generalized extreme value (GEV) distribution, Indo-Pacific Ocean, wind-sea and swell SWH
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