Coastal and Ocean Data Assimilation: An Introduction to the Analysis, Interpolation, and Assimilation of Space-Time Data
MIAMI UNIV FL ROSENSTIEL SCHOOL OF MARINE AND ATMOSPHERIC SCIENCE
Pagination or Media Count:
Our primary goal is to publish a textbook on analyzing, interpolating, and assimilating space-time data. The textbook will be submitted for publication by Cambridge University Press, who has already expressed an interest in publishing the book. This new textbook will be an up-to-date reference on both classical methodologies and new novel techniques for the analysis, interpolation, and assimilation of space-time data. Many of the new techniques described in this textbook were developed under ONR funding. Our primary objective is to develop new, multi-scale data assimilation algorithms for both Eulerian and Lagrangian prediction in coastal, ocean, and in transition regions that optimizes the information from measurements with different error and sampling characteristics. In particular, how to both combine and assimilate measurements that measure much different scales of motion in domains dominated by heterogeneous, broad-band dynamics. These methods will form the core of the textbook. Our approaches are based on customizing, for Naval oceanographic applications, the latest developments in signal processing and Bayesian Analysis. In particular, the use of the reduced-order information filter ROIF for high-resolution data assimilative modeling, and the re-sampled particle filter RPF for the inverse Lagrangian prediction problem.
- Physical and Dynamic Oceanography
- Numerical Mathematics