Understanding Tidal And Non-Tidal Representation Of Numerical Model Using Data Relationship Analysis In Singapore Regional Waters

Alamsyah Kurniawan, Seng Keat Ooi, Vladan Babovic

Friday 3 july 2015

11:45 - 12:00h at Central America (level 0)

Themes: (T) Water resources and hydro informatics (WRHI), (ST) Management support systems and serious gaming

Parallel session: 15H. Water resources - Serious gaming

The application of ocean-atmosphere coupling through tidal and non-tidal barotropic numerical modelling to forecast sea level in Singapore Regional Waters have greatly improved the understanding of the factors and mechanisms influencing of sea level in Singapore Strait. However, complex governing mechanisms, multi-scale, multi-dimensional, time varying, and highly non-linear dynamics of the marine systems make the oceanographic modelling efforts much more challenging. Hence, there is an increasing need for alternate approaches which can provide vital information leading to better domain knowledge and reduced time and effort required to tune the numerical models. With increasing spatial and temporal data coverage, better quality and reliability of data modelling and data driven techniques are becoming more favourable and acceptable to the hydrodynamic community. The data mining tools and techniques are being applied in variety of hydro-informatics applications ranging from simple data mining for pattern discovery to data driven models and numerical model error correction. The present study explores the feasibility of applying mutual information theory by evaluating the amount of information contained in observed and prediction of tidal and non-tidal barotropic numerical modelling by relating them to variables that reflect the state at which the predictions are made such as input data, state variables and model output.