Patrikalakis, N.M., P.F.J. Lermusiaux, C. Evangelinos, J.J. McCarthy, A.R. Robinson, H. Schmidt, P.J. Haley, S. Lalis, R. Tian, W.G. Leslie, and W. Cho, 2009.
Towards Dynamic Data Driven Systems for Rapid Adaptive Interdisciplinary Ocean Forecasting Invited paper in "Dynamic Data-Driven Application Systems''. F. Darema, Editor. Springer, 2009. In press.
The state of the ocean evolves and its dynamics involves transitions occurring
at multiple scales. For efficient and rapid interdisciplinary forecasting, ocean
observing and prediction systems must have the same behavior and adapt to the everchanging
dynamics. The work discussed here aims to set the basis of a distributed
system for real-time interdisciplinary ocean field and uncertainty forecasting with
adaptive modeling and adaptive sampling. The scientific goal is to couple physical
and biological oceanography with ocean acoustics. The technical goal is to build a
dynamic system based on advanced infrastructures, distributed / grid computing and
efficient information retrieval and visualization interfaces. Importantly, the system
combines a suite of modern legacy physical models, acoustic models and ocean current
monitoring data assimilation schemes with new adaptive modeling and adaptive
sampling methods. The legacy systems are encapsulated at the binary level using
software component methodologies. Measurement models are utilized to link
the observed data to the dynamical model variables and structures. With adaptive
sampling, the data acquisition is dynamic and aims to minimize the predicted uncertainties,
maximize the sampling of key dynamics and maintain overall coverage.
With adaptive modeling, model improvements are dynamic and aim to select the
best model structures and parameters among different physical or biogeochemical
parameterizations. The dynamic coupling of models and measurements discussed
here represents a Dynamic Data-Driven Application System (DDDAS). Technical
and scientific progress is highlighted based on examples in Massachusetts Bay, and
Monterey Bay and the California Current System.
Keywords: Oceanography, interdisciplinary, adaptive, sampling,