P-2

Emerging Data Assimilation for interdisciplinary Systems

Balla Maggero (Ocaen Data Assimilation Research, R&D Department , Institute of Meteorological Training & Research )

Identification, understanding, and prediction of many interdisciplinary oceanographic processes continue to be elusive goals of ocean science. However, new technology is being effectively applied to increase the variety and numbers of sampled variables and thus to fill in the gaps of the time-space continuum of interdisciplinary ocean observations. The formulation, precision, and efficiency of data assimilative models are highly dependent upon the quality and quantity of interdisciplinary observational data. With computing power rapidly advancing, coupled interdisciplinary research on both fundamental dynamics and applications is becoming the new frontier in ocean investigation. This poster presents emerging capabilities and their optimal utilization in data assimilative models. These concepts are developed within the framework of an interdisciplinary system for assessing acoustic system performance. An end-to-end system, that couples meteorology-ocean physics- acoustics-bottom-noise-target data and dynamic models, is used to estimate uncertainties with the boundary traffic and received echoes. The approach involves a full, interdisciplinary state vector and error covariance matrix. An example of resultant picture system is given based upon the Shelfbreak PRIMER data and indormation.