Characteristics of shallow water waves off the central west coast of India before, during and after the onset of the Indian summer monsoon

Amrutha, M. M.; Kumar, V. Sanil; Sharma, Sheela; Singh, Jai; Gowthaman, R.; Kankara, R. S.

doi:10.1016/j.oceaneng.2015.07.061

Cited by 23 publications

(7 citation statements)

References 22 publications

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“…They were predominantly from the west-southwest direction ( Figure 3) due to the dominance of swells in the west coast of India during this season [21,48]. The T m02 during monsoon varied from 3.4 to 9.7 s with an average value of 6.2 s (Figure 2b The highest Hs of about 2 m along the study region during non-monsoon months was previously reported by Amrutha et al [25] and the existence of long-period waves (Tp > 18 s) along the eastern Arabian sea was also previously reported [49,50]. Tm02 values observed off Vengurla are similar to the value (7-8 s) observed off the Goa coast [46].…”

Section: Wave Characteristics At 15 M Water Depthsupporting

confidence: 63%

“…2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse [31]. High wave activity (seasonal average Hs ~2 m) is experienced during monsoon and calm wave conditions (Hs < 1 m) during the remaining period of the year [25]. Based on Davies classification [33,34], the wave and tide data together exhibit that the study area is on a microtidal wave-dominated coast and the predominant breaker is a plunging breaker with multiple breakers [35].…”

Section: Study Areamentioning

confidence: 99%

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Nearshore Waves and Littoral Drift Along a Micro-Tidal Wave-Dominated Coast Having Comparable Wind-Sea and Swell Energy

George

Kumar

Gowthaman

et al. 2020

JMSE

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The nearshore wave characteristics and variations in littoral drift (longshore sediment transport; LST) are estimated based on different approaches for four years along the Vengurla coast, with comparable wind-sea and swell energy assessed. The waverider buoy-measured data at 15 m water depth is utilized as the input wave parameters along with the reanalysis model data, and the numerical wave model Delft-3D is used for estimating the nearshore wave parameters. The relative contribution of wind-seas and swells on LST rates are specifically examined. The clear prevalence of west-southwest waves implies the prevalence of south to north longshore sediment transport with net transport varying from 0.19–0.37 × 105 m3/yr. LST is strongly dependent on the breaker angle and a small change in the wave direction substantially alters the LST, and hence reanalysis/model data with coarse resolutions produce large errors (~38%) in the LST estimate. The annual gross LST rate based on integral wave parameters is only 58% considering the wind-seas and swells separately, since the wind-sea energy is comparable to swell energy, and the direction of these two systems differs significantly.

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Section: Wave Characteristics At 15 M Water Depthsupporting

confidence: 63%

Section: Study Areamentioning

confidence: 99%

Nearshore Waves and Littoral Drift Along a Micro-Tidal Wave-Dominated Coast Having Comparable Wind-Sea and Swell Energy

George

Kumar

Gowthaman

et al. 2020

JMSE

Self Cite

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“…This includes, but is not limited to, calculations of wave loads on coastal structures; calculations of sediments and pollutants transports in coastal areas, real time swell forecasting, safety of maritime transportation, fishing industry, validation of wave prediction models [5][6][7][8][9].Surface waves have very complex natures and are highly irregular with respect to their height, direction, amplitude and period [10]. The direct measurements of these parameters are now carried out either by directional or non-directional instruments such as wave buoys or bottom-mounted acoustic Doppler transceivers.…”

Section: Introductionmentioning

confidence: 99%

General Characteristics of Surface Waves off Port Said, Egypt

Elsharkawy¹,

El-Geziry²,

El-Din³

2016

IOSR

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“…Changes in the wave climate are related to changes in the local or remote wind forcing. The changes that we observe in the waves of eastern AS during the ISM are studied extensively (Sanil Kumar et al, 2003Chempalayil et al, 2012;Glejin et al, 2013;Amrutha et al, 2015). The inter-annual and inter-decadal variability in the significant wave heights of the north Indian Ocean during 1979 to 2012 is studied .…”

Section: Introductionmentioning

confidence: 90%

“…The variability of wave heights in the North Atlantic are linked to the North Atlantic Oscillation (NAO) (Izaguirre et al, 2011). Higher waves are reported in the eastern North Pacific during major El Niño events (Allan and Komar, 2000). Izaguirre et al (2011) studied the extreme wave height variability on the global scale including the Indian Ocean sector using 10 global climatic indices and reported that the Antarctic Oscillation (AO), Southern Annular Mode (SAM), and ENSO are the most influential climate patterns influencing the inter-annual variability of extreme wave heights around the globe.…”

Section: Introductionmentioning

confidence: 99%

Influence of Indian summer monsoon variability on the surface waves in the coastal regions of eastern Arabian Sea

Kumar

George

2016

Ann. Geophys.

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Abstract. We assess the influence of monsoon variability on the surface waves using measured wave data covering 7 years and reanalysis data from 1979 to 2015 during the Indian summer monsoon (JJAS) in the eastern Arabian Sea. The interannual comparison shows that the percentage of higher wave heights ( > 2.5 m) is higher (∼ 26%) in 2014 than in other years due to the higher monsoon wind speed (average speed ∼ 7.3 m s −1 ) in 2014. Due to the delayed monsoon, monthly average significant wave height (H m0 ) of June was lowest (∼ 1.5 m) in 2009. The spectral peak shifted to lower frequencies in September due to the reduction of wind seas as a result of decrease in monsoon intensity. The study shows high positive correlation (r ∼ 0.84) between average lowlevel jet (LLJ) for the block 0-15 • N, 50-75 • E and H m0 of eastern Arabian Sea in all the months except in August (r ∼ 0.66). The time series data on wave height shows oscillations with periods 5 to 20 days. Wavelet coherence analysis indicates that the LLJ and H m0 are in-phase related (phase angle 0 • ) almost all the time and LLJ leads H m0 . The monsoon seasonal anomaly of H m0 is found to have a negative relationship with the Oceanic Niño Index indicating that the monsoon average H m0 is relatively low during the strong El Niño years.

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Characteristics of shallow water waves off the central west coast of India before, during and after the onset of the Indian summer monsoon

Cited by 23 publications

References 22 publications

Nearshore Waves and Littoral Drift Along a Micro-Tidal Wave-Dominated Coast Having Comparable Wind-Sea and Swell Energy

Nearshore Waves and Littoral Drift Along a Micro-Tidal Wave-Dominated Coast Having Comparable Wind-Sea and Swell Energy

General Characteristics of Surface Waves off Port Said, Egypt

Influence of Indian summer monsoon variability on the surface waves in the coastal regions of eastern Arabian Sea

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