Dipole behaviour in maximum significant wave height over the Southern Indian Ocean

Abstract

The study reports on existence of a dipole pattern in maximum significant wave height (MSWH) as well in mean significant wave height over the Southern Indian Ocean (SIO) based on analysis using 24 years of satellite observations. Analysis using quality checked daily altimeter data from nine satellite missions for entire Indian Ocean region revealed the spatio-temporal variability of observed dipole phenomena. Interestingly, the second empirical orthogonal function (EOF) mode (EOF2) in monthly and monthly anomaly MSWH data clearly shows the prevalence of dipole over the SIO having a period of 6 months for monthly dataset Principal Component (PC) leading to a 3 months oscillation. The EOF of monthly anomaly dataset analysis also exhibited a similar dipole pattern for the EOF2 mode having a period of 2.1 years. In addition, the study also considered seasonal EOF analysis for four austral seasons December-January-February (DJF), March-April-May (MAM), June-July-August (JJA), and September-October-November (SON). The EOF2 for all seasons exhibits a similar dipole pattern in SIO basin, except for the DJF months. Based on seasonal EOF analysis, the DJF and JJA EOF2s have similar dipole pattern that reverses its polarity because of wind variability for the MAM and SON EOF2s justifying 3 months dipole oscillation obtained for monthly datasets. The Radon transform is used to investigate the orientation of this dipole, and for the first time this method is used in the field of climatology to study orientation and the degree of polarity of a dipole pattern. Furthermore, the study investigated possible correlation of dipole with various proven climate indices establishing the fact that Southern Annular Mode Index (SAMI) showed a significant correlation. The other seasonal datasets also correlated well with SAMI, except DJF months that do not show the dipole pattern, and it had a good correlation with Nino3 index representing the El Nino Southern Oscillation Index.

Climatic, Decadal, and Interannual Variability in the Upper Layer of the Mediterranean Sea Using Remotely Sensed and In-Situ Data

“…The signatures of the strong MHWs that occurred in 2003, 2006, and 2017 [17,80,82] are clearly visible in the WMED and CMED, while they are not detected in the EMED (Figure 9B). On the other hand, the event of 2010 [64] involves only the EMED, while that of 2012 [81] involves both CMED and EMED.…”

“…The spatial-temporal variations of these parameters were obtained by performing an empirical orthogonal function s (EOFs) analysis [62] to the gridded monthly datasets. EOF analysis is one of the most widely used and accepted methods to understand the variability in climate data (e.g., Hannachi et al [63]; Gupta et al [64]). This method essentially captures the nonlinearity and high-dimensional characteristics for a given dataset, preserving significant patterns and their variability, thereby aiding the users to derive meaningful information for data interpretation and analysis (e.g., Hannachi et al [63]; Gupta et al [64]).…”

“…EOF analysis is one of the most widely used and accepted methods to understand the variability in climate data (e.g., Hannachi et al [63]; Gupta et al [64]). This method essentially captures the nonlinearity and high-dimensional characteristics for a given dataset, preserving significant patterns and their variability, thereby aiding the users to derive meaningful information for data interpretation and analysis (e.g., Hannachi et al [63]; Gupta et al [64]). The EOFs method finds the spatial patterns of variability and their time variations, and gives a measure of the "importance" of each pattern [65].…”

Influence of climate variability on wind‐sea and swell wave height extreme over the Indo‐Pacific Ocean

“…Prior studies have investigated the extreme wind‐wave conditions at global (Young et al ., 2011; Dobrynin et al ., 2012; Kumar et al ., 2016) and regional scales (Allan and Komar, 2000; Nayak et al ., 2012; Shanas and Kumar, 2014a, 2014b; Li et al ., 2016; Gupta et al ., 2017). Takbash and Young (2020) identified an overall increasing trend in wave height extremes over the Southern Hemisphere, yet a decreasing trend over the Northern Hemisphere.…”

Wave–current-surge interaction in a changing climate over a shallow continental shelf region

“…Several studies have investigated the extreme wave characteristics over the North Indian Ocean region. Some of the studies include Bhaskaran et al (2000Bhaskaran et al ( , 2004Bhaskaran et al ( , 2013aBhaskaran et al ( ,b, 2015, Bhaskaran (2010Bhaskaran ( , 2019, Gayathri et al (2015Gayathri et al ( , 2016, Gupta et al (2015Gupta et al ( , 2017, Murty et al (2016Murty et al ( , 2019Murty et al ( , 2020, Nayak et al (2012Nayak et al ( , 2013, Nayak and Bhaskaran (2014), Padhy et al (2008), Patra and Bhaskaran (2016a,b), Patra et al (2019), Poulose et al (2017), Samiksha et al (2017) and Umesh et al (2019). Literature survey provides no background studies that links impact of climate change on coastal hydrodynamics for the shallow shelf region between India and Sri Lanka.…”