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Extreme Wave Height Analysis in Natuna Sea Using Peak-Over Threshold Method
Jabbar I.A.a, Ningsih N.S.a
a Study Program of Oceanography, Faculty of Earth Sciences and Technology, Bandung Institute of Technology, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© Published under licence by IOP Publishing Ltd.Extreme wave height analysis has been conducted in Natuna Sea, Indonesia, using 25 years (1991-2015) significant wave height (SWH) data from WAVEWATCH 3 (WW3) with a spatial resolution of 1/8°. The Natuna Sea is geographically connected to South China Sea (SCS) and is often crossed by tropical cyclones. These cyclones may have contributed to the existences of high waves in the SCS, which can propagate as swell waves to the Natuna Sea and can lead to extreme waves in this region. The extreme analysis has been done by classifying extreme events of SWHs using Peak-Over Threshold (POT) method with a fixed threshold level at quantile 0.93 and a minimum time separation of 48 hours between two successive extreme events. Furthermore, Generalized Pareto (GP) distribution has been applied to estimate return values of the extreme SWHs for several return periods. Parameters of the GPD have been estimated by Maximum Likelihood Estimation (MLE) method. Characteristics of extreme SWHs in the Natuna Sea have been explained by maximum and seasonal distribution plots. The maximum value of extreme SWHs in the SCS can reach 13 m and around 3-5 m in the Natuna Sea. The seasonal distributions of extreme waves indicate that the occurrences of extreme waves in the SCS during Northeast Winter Monsoon (NWM) are higher than those during Southwest Summer Monsoon (SSM). Seasonal mean and maxima of extreme SWHs in the Natuna Sea are also high during the NWM and low during the SSM. To examine the effects of swell waves from the SCS and also future extreme waves in the Natuna Sea, we have analyzed the characteristics and calculated return values of extreme waves in front and behind of Bunguran Island, which the former faces directly to the SCS. There were 172 (331) extreme waves from 1991-2015 in the front (behind) of Bunguran Island and mainly from the northeast (southwest). Most of them were around 2 – 4 (0.5 – 2) m with mean periods of 6 – 10 (3 – 6) s. Based on the return values in the front (behind) of the Bunguran Island, there are possibilities of extreme waves with values 4.70, 4.87, and 4.96 (2.08, 2.20, and 2.27) m for return periods of 25, 50, and 75-year, successively.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Extreme wave heights,Fixed threshold,Peak over threshold,Peak over threshold method,Seasonal distributions,Significant wave height,Spatial resolution,Tropical cyclone[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]Parts of this research were funded by the Ministry of Research, Technology, and Higher Education (Kemeristekdikti) of the Republic of Indonesia under Basic Research Grant 2019. The authors would like to thank the supports of Kemenristekdikti. The authors also would like to thank Dr. Ibnu Sofian from the Geospatial Information Agency (BIG) for providing the WW3 SWH data.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1755-1315/618/1/012024[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]