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

2019

JGR Oceans

Self Cite

Nearshore wave characteristics and its variations at Ganpatipule coast, eastern Arabian Sea, for the past 4 decades (1979–2016) have been examined. The study is based on European Centre for Medium‐Range Weather Forecasts Re‐Analysis‐Interim wave data at ~50 m water depth and the nearshore wave parameters estimated using the numerical model Simulating WAves Nearshore, executed from the Delft3D dashboard considering shallow water wave propagation, wave setup, and breaking. The littoral drift is estimated based on bulk transport formula of the Coastal Engineering Research Centre with the input from the hydrodynamic module. The model shows good agreement with wave rider buoy measured wave parameters at 14‐m water depth. Anomalies of breaker height, period, and direction vary in the range of −0.35–0.4 m, −0.80–1 s, and − 16 to 12°, respectively during the study period. A detailed analysis of monthly variations of breaker height along the study region suggests a significant increasing trend during the Asian summer monsoon, whereas a decreasing trend is identified during the nonmonsoon period. The study region accounts for a northerly net transport of 3.9 × 105 m3 yr−1 with a significant increasing trend of 1,840 m3 yr−1. The strong wind field region along the central Arabian Sea (65–70°E and 15–20°N) gives a strengthened positive correlation (r > 0.7) with the littoral drift. Impacts of Pacific climate variability on interannual and decadal timescales are observed in the littoral drift rates.

Section: Regional Climate Influencementioning

confidence: 93%

Section: Long-term Variations In Nearshore Characteristicsmentioning

confidence: 98%

Long‐Term Variations in Nearshore Wave Climate and Littoral Drift at Ganpatipule Coast, Eastern Arabian Sea and its Link to Pacific Climate Variability

George

2019

JGR Oceans

Self Cite

“…The maximum monthly average SWH in the study area (1.56 m) is less than the value (1.84 m) observed in the eastern AS (Honnavar) during the same period (Figure 6a). In the eastern AS, the annual maximum monthly average SWH is 2.1 m and is observed in June (Sanil Kumar and George, 2016), whereas the corresponding value for the study area in June is 1.48 m. In November, the monthly average SWH is 1.1 m in the study area, whereas it is 0.5 m in the eastern AS. The annual average SWH of the study area (~1 m) is similar to that for the eastern AS.…”

Section: Variations In Bulk Wave Parametersmentioning

confidence: 75%

Features of locally and remotely generated surface gravity waves in the inner‐shelf region of northwestern Bay of Bengal

Nair

Intl Journal of Climatology

Amrutha

et al. 2018

In this article, we studied the characteristics of locally and remotely generated wind waves in the inner‐shelf region of northwestern Bay of Bengal (BoB) based on the measured wave data. Two well‐differentiated wave systems, one young sea from the east‐southeast and another more developed swell from the south lead to bimodality in the wave spectrum. Wind‐sea predominance is not observed in the monthly average wave spectrum and in all the months swells dominated indicating a swell‐driven wave regime. During the monsoon (JJAS), the wave climate is dominated by long‐period swell from the south‐southeast and the short fetch during the northeast monsoon (ONDJ) leads to weaker easterly swells, while the effects of the sea/land breeze influence on the wave generation are more relevant during this season. During November–April, diurnal variation of 0.15 m in significant wave height (SWH) is observed. The study based on seasonally averaged ERA‐Interim reanalysis data reveals a weak connection between the waves in the northwestern BoB and the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events. The waves are influenced by ENSO events during June–September and by IOD events during October–January, which consequently caused inter‐annual variations in monthly average SWH. The present study, however, did not show a significant inter‐annual variability in annual mean SWH during 1979–2015.

“…The spectral analysis results in wave spectrum with a resolution of 0.005 Hz from 0.025 Hz to 0.1 Hz and after that, it is 0.01 Hz up to 0.58 Hz (Datawell, 2009). The H s , mean wave period (T m02 ) 15 and spectral peak period (T p ) are estimated from the variance density spectrum of surface elevation for data covering 30-minutes. From the half hourly wave spectra, the 90, 75, 50 and 25 percentile wave spectra are also computed by taking the respective variance density of each frequency bin for all high waves (H s > 3 m).…”

Section: Methodsmentioning

confidence: 99%

“…However, understanding the crest height variation of the surface waves remains a major challenge in offshore and nearshore industry due to limited measured time series surface elevation data. 15 Since the measured wave data are not available for large areas, satellite observations and wave hindcast models are used in deriving the wave parameters (Shanas et al, 2014). The numerical models have become a tool to get long-term wave information in high-resolution (spatial and temporal) in areas devoid of measurements (Appendini et al, 2014).…”

mentioning

confidence: 99%

Characteristics of high monsoon wind-waves observed at multiple stations in the eastern Arabian Sea

Amrutha

2017

Preprint

Abstract. The growth and decay of surface wind-waves during one-month period in a typical Indian summer monsoon is investigated based on the data collected at 9 to 15 m water depth at 4 locations in the nearshore waters of the eastern Arabian Sea covering a spatial distance of ~350 km. The significant wave height varied from 0.7 to 5.5 m during the data collection considered in the analysis. The heights of waves during the measurement period often exceed 3 m. The most extreme wave 10 height is 1.50 to 1.62 times the significant wave height and the most extreme crest height of the wave is 1.23 to 1.35 times the significant wave height of the same 30-minutes record. The average ratio of crest height of the wave to the height of the same wave is 0.58 to 0.67. The height of waves having maximum crest height is smaller than the maximum wave height during 30 minutes period. Measured waves are predominantly swell, but since the majority of wave generation during the monsoon is adjacent to the study area and the wind-wave coupling is strong, wave periods are rarely above 15 s. The 15 numerical wave model could estimate the wave height reasonably well during the wave growth compared to the wave decay period. Hovmöller diagrams show a considerable spatial variability in the wave and wind pattern in the Indian Ocean during the high wave event at the eastern Arabian Sea.