Storm Surge Modeling in the Southern of Java using Coupled 4D-VAR Circulation-Waves Model : EnsembleKF and Multi-Verification Approach

Ejha Larasati Siadari, Indonesian Agency for Meteorology, Climatology and Geophysics, Center for Marine Meteorology, Jakarta, Indonesia, Nelly Florida Riama, Indonesian Agency for Meteorology, Climatology and Geophysics, Education and Training, Jakarta, Indonesia and Mr. Khafid Rizki Rizki Pratama, Indonesian Agency for Meteorology, Climatology and Geophysics BMKG, Jakarta, Indonesia
Abstract:
Indonesian Maritime Continent is a complex substance with the highest mean high water datum on coastal area throughout the year. There are 2 research focuses: (1) Improving the initials of the input system in the ADCIRC-SWAN model. The assimilation was applied based on the in-situ observations data for improving the accuracy. The research of storm surge modeling in the southern coastal region of Java was carried out by the integration of the 4DVAR assimilation technique of the surface observation and Sentinel-SAR/1B altimeter satellite data into the Advanced Circulation and Simulating Waves Nearshore (ADCIRC-SWAN) model. The finite-volume grid domain pattern with domain density of 150 meters and use of S2, M2, O2 semi-diurnal tidal components for open boundaries. The output of the ADCIRC-SWAN model is tidal and coastal inundation conditions. The deep water waves pattern as the output of WaveWatch 3 model is used to analyse its influence to the formation of fully-developed sea propagation and the swell profile in coastal area. The increase in sea level and peak surge is dominantly caused by friction effect from the strong wind-driven intensity on sea surface. It causes an fluctuation in tides of 20-30 cm after the Ernie tropical cyclone event on April 6-10, 2017. (2) The verification of EnsembleKF uses 5 member verifiers and wave spectre of Sentinel-SAR/1B satellite data is used as a comparison to the SWAN model output of shallow water with a multi-verification approach of synoptic and in-situ observation.