Waves off Gopalpur, northern Bay of Bengal during Cyclone Phailin

2019

Various engineering activities in a coastal and offshore environment require detailed assessment about the probable extreme wave characteristics in its lifetime to prevent human as well as property loss. The accurate estimation of wave height with a 100‐year return period not only contribute to the level of protection but also the scale of investments. In this study, significant wave height return levels for a northwestern Bay of Bengal location are estimated using extreme value models; generalized extreme value (GEV) and generalized Pareto distribution (GPD). Both block maxima and initial distribution methods are used in the GEV and GPD incorporated with peak over threshold (POT) series. The study is based on the European Centre for Medium‐Range Weather Forecasts ERA5 reanalysis hourly data at 0.25° × 0.25° spatial resolution from 1979 to 2017. The GPD estimates show that the return levels do not follow prevailing seasonality over the location since the return levels greatly depend upon the extreme events and most of the extreme events are during the northeast monsoon season (October–January). The POT with October–January data gives 9.08 m as 100‐year return level, and corresponding Indian southwest monsoon (June–September) return level is only 5.41 m. When different block periods ranging from 15 to 39 years are considered, the 50‐year return levels range from 5.12 to 8.67 m for GEV with annual maxima. The influence of tropical cyclones (TCs) on return levels are examined considering different case studies, and the results show that the strength of a TC alters the return levels more significantly than the number of TCs in the observation. The 100‐year return level decreases by ~30% when wave height during the two cyclones; Phailin and Hudhud are removed from the data set.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of tropical cyclones on the 100‐year return period wave height—A study based on 39‐year long ERA5 reanalysis data

Naseef

2019

“…Observational wave data in the BoB are sparse. Only few wave buoy records exist, and these are intermittent (Sanil Kumar et al, , ; Suresh et al, ; Johnson et al, ; Amrutha et al, ; Patra et al, ). Sanil Kumar et al .…”

Section: Introductionmentioning

confidence: 99%

“…Observational wave data in the BoB are sparse. Only few wave buoy records exist, and these are intermittent (Sanil Kumar et al, 2001Suresh et al, 2010;Johnson et al, 2013;Amrutha et al, 2014;Patra et al, 2016). Sanil reported that the seasonal average value of significant wave height (SWH) varied from 0.8 m in the northeast (NE) monsoon season (ONDJ) to 1.3 m in the southwest (SW) monsoon season (JJAS) along the northwestern BoB.…”

Section: Introductionmentioning

confidence: 99%

“…Whereas, BoB is the region where the deadliest tropical cyclones (TCs) (generally referred to as a hurricane in the Atlantic and the Eastern Pacific and a typhoon in the Western Pacific) occurred (Balaguru et al, 2014). During the TC, high waves with SWH of~6 to 8 m were measured in the BoB (Amrutha et al, 2014). The occurrence of TCs in BoB is high in May and in October-November, indicating an annual bimodal structure (Balaguru et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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

Nair

Amrutha

et al. 2018

Self Cite

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.

Climatology and trends of the Indian Ocean surface waves based on 39‐year long ERA5 reanalysis data

Naseef

2019

Self Cite

In this study, the wind and the surface waves in the Indian Ocean (IO) during 1979–2017 are studied based on the ECMWF ERA5 Reanalysis data. Long‐term statistical analysis of extreme waves is carried out based on Generalized Extreme Value distribution using annual maxima and the spatial distribution of return levels for 50 and 100 years are studied. In general, the ERA5 significant wave height (Hs) and maximum wave height (Hmax) show a good agreement with measured buoy data in the coastal (bias ~0.29 m) and deep waters (bias ~0.18 m). During the tropical cyclone, underestimation of Hs and Hmax in the ERA5 data compared to buoy data is 2.7 and 1.4%, but in general the bias is large (~0.69 m). Swell domination is observed in larger regions of the IO, whereas wind‐seas are comparable to swells in the Southern Ocean. The meridional wind speed largely influences the spatial pattern of Hs in the North IO. The stronger winds over the Southern Ocean play a major role in generating higher waves at higher latitudes. Maximum value of the 100‐year return level for Hs in IO is 17.8 m, whereas highest value of the Hs is 16.7 m and Hmax is 32.0 m. Severe wave events are common at 50°–60°S and only during 25% of the time in a year, Hmax is less than 5 m in this region. Ratio of the Hmax to Hs varies from 1.46 to 2.3 with a mean value of 1.87. The 100‐year return value of Hs changed by −4 to 5 m, when the length of the dataset is decreased from 39 years (1979–2017) to recent 20 years. On an average, from 1979 to 2017, the annual average Hmax increased by 0.73 cm/year. In major areas of the IO, a clear decrease of the Hs is observed during 1991–2017, whereas during 1979–2017, an increase in Hs is found.