Nur, A.A.; Suprijo, T.; Mandang, I.; Radjawane, I.M.; Park, H., and Khadami, F., 2021. Ocean modeling in the Makassar Strait and Balikpapan Bay using online nesting method. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 206–210. Coconut Creek (Florida), ISSN 0749-0208.
This study had applied offline nesting method (one-way interaction) by using Regional Ocean Modeling System (ROMS) to simulate currents circulation in the Balikpapan Bay and showing good results with a high agreement between model output and observational measurement for water level data. It proves that even using the offline nesting method is the better option than increasing grid resolution on the entire model domain that will be demanding more computational cost, while the area of interest is a small-scale application. Therefore, this study aims to improve the model solution by using the online nesting method (two-way interaction) with a refinement ratio of 1:5 from the larger domain to a smaller domain. Three domains which include larger domain (L1) with spatial resolution 2.5 km that encompasses almost the entire Makassar Strait and acted as parent grid for the model. Coarser model of domain L2 with 500 m resolution becomes the buffer zone between the parent model (L1) and smaller domain (L3) in the Balikpapan Bay that has 100 m resolution. Initial and boundary conditions (IC/BC) for the L1 domain consisting of water levels, currents, temperature, and salinity were derived from the Hybrid Coordinate Ocean Model (HyCOM) re-analysis dataset. By using this method, there is only IC needed to be prepared for the other domain by interpolating IC data from the L1 domain and the BC would be provided directly from their larger domain during the simulation. Surface forcing for all domains extracted from the European Centre for Medium-Range Weather Forecast (ECMWF) ERA5 hourly dataset. Statistical methods such as Root Mean Square Error (RMSE) and model skill were used to validate model results for each model domain and found the improvement of the model solution when comparing observational data by model results for the larger and smaller domain at the same location, respectively.