KM Sinar Bangun IV yang mengangkut penumpang sebanyak 188 orang dan 70 unit kendaaan diberitakan tenggelam di Danau Toba pada hari Senin tanggal 18 Juni 2018. Kejadian itu diprakirakan terjadi akibat adanya kelebihan kapasitas muatan, kondisi cuaca yang buruk, dan human error. Analisis cuaca baik dalam skala global, regional, maupun lokal dilakukan untuk mengetahui kondisi cuaca saat kejadian. Analisis data citra satelit, AWS, dan ARG digunakan untuk mengetahui kondisi cuaca juga. Berdasarkan analisis streamline terdapat shearline di sekitar wilayah Sumatera Utara yang dapat memicu pertumbuhan awan cumuliform khususnya awan Cumulonimbus. Suhu permukaan laut dalam kondisi hangat yaitu berkisar 28 − 30 o C sehingga konvektifitas antara atmosfer dan lautan cukup giat. Berdasarkan analisis time series suhu puncak awan dari kanal IR dan VIS, menunjukkan adanya pertumbuhan awan konvektif di sekitar Danau Toba. Pada saat kejadian, wilayah di sekitar Danau Toba sedang terjadi hujan dimana beberapa AWS dan ARG mencatat curah hujan yang mencapai lebih dari 30 mm/hari. Kata Kunci : cuaca buruk, himawari-8, satelit.Abstract KM Sinar Bangun IV was carrying passengers about 188 people and 70 units of vehicles when it sank in Lake Toba, North Sumatra on Monday, June 18, 2018. The incident was occurred due to overcapacity, bad weather condition, and human error. Meteorological analysis on a global, regional and local scales were used to determine atmospheric dynamics at the time of the event. Meanwhile, Satellite, AWS, and ARG data were used to determine the weather condition. Streamline analysis showed the shear line pattern in Sumatra Island and convergence in North Sumatra. The condition of sea surface temperature was warm enough in the range of 28 − 30 o C. These conditions triggered for the potential of convective clouds development. Himawari-8 satellite images from IR and VIS channels showed the development of convective clouds in Lake Toba right before the event happened. AWS and ARG measurements around the Lake Toba area recorded precipitation which the value was greater than 30 mm/day.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.