Radar Research, Results & Data to Decisions - R3D2

The R3D2 project will develop advanced synthesised data products from what are currently research and development grade wave inversion outputs of remotely sensed water depth maps and currents.
Wave inversion methods have been developed at the NOC for over two decades and are now able to derive depth and current-vector maps over ranges up to 6km from both static (land based) radars, and more recently from moving vessels. Sequences of radar backscatter images are processed to extract wave lengths, periods and directions that are fitted to linear wave theory. Under ideal conditions, results match well with survey depths and currents measured by ADCP.
There is a developing demand by potential users for these capabilities to be available as a commercial service and the NOC have partnered with Marlan Maritime Ltd to deliver this. Under the operational conditions dictated by user needs, the requirement has been increasingly to attempt to operate under lower and lower wind and sea states and in areas in which the radar imaging mechanism struggles to detect adequate wave signatures as inputs to the algorithms. This has inevitably led to challenges determining when the algorithms are producing estimates of depth and currents that are consistent with reality - a situation that needs to be addressed if the user community is to continue adopting these disruptive methods.
Unpublished work at the NOC has previously shown that a range of quality and confidence measures combined with elements of machine learning help to stabilise and quality control time series of results as the algorithms 'learn' the characteristics of each site.