Oceanographic features such as jets and vortices are often found downstream of obstacles and landforms such as islands or peninsulas. Such features have high spatial and temporal variability and are, hence, interesting but difficult to measure and quantify. This paper discusses an experiment to identify and resolve such oceanographic features in Selat Pauh, in the Straits of Singapore. The deployment formation for multiple robotic vehicles (Autonomous Surface Craft - ASC), the measurement instruments, and the algorithms developed in extracting oceanographic field variables are described. These were based on two ocean field predictions from well-known geophysical flow dynamic models. Field experiments were carried out and comparison of the forecasts with measurements was attempted. To investigate an unexpected behaviour of one ASC, hindcasts with wind effects and simulation with vortex feature extraction on a larger domain with more involved bathymetry were also partially carried out.
This paper describes work in progress under a research initiative funded by Singapore's National Research Foundation. This has led to the establishment of the Singapore-MIT Alliance for Research and Technology (SMART, 2008) and the creation of MIT's first research center outside the USA. One of the interdisciplinary research projects within SMART is the Center for Environmental Sensing and Modeling (CENSAM, 2008). One component of CENSAM involves oceanographic modeling, forecasting and experimentation with a network of robotic vehicles both surface and underwater. The overall objective of this part of the project is to develop adaptive sampling and assimilation strategies that would enhance our ability to forecast physical, chemical and biological oceanography fields through suitable optimized use of the measurement resources operating in a coupled fashion with computational models of the dynamic ocean behavior. This paper describes recent collaborative research and experiments over the last twelve months, carried out by MIT scientists and engineers and counterparts at the National University of Singapore (NUS). The overall project involves 4 professors, 2 research scientists, 3 postdoctoral associates, 6 research engineers and 2 PhD students.
