OCEAN STATE ESTIMATION FOR UNDERSEA REMOTE SENSING
Abstract
Our long term goal is to gain a quantitative understanding of the environmental conditions at complex coastal sites (e.g. tidal inle"ts), including information about bathymetry and 3D hydrodynamic conditions (i.e. wave field and circulation) using a combination of" numerical models and remote sensingmeasurements of the ocean surface along with any needed selected in-situ observations. Our specific objectives involve applying previously developed methodologies for the prediction of the state of the ocean near inlets using coupled wave and circulation models and remote sensing observationsas well as selected in-situ data obtained during the Undersea Remote Sensing (USRS) DRI. This workwill be carried out with an eye towards improved acoustical characterization of the environment. Theprimary objectives are:1. Adapt our data assimilative (DA) system (consisting of a combination of numerical models andremote sensing and selected in-situ data) in order to obtain an estimate of the underlyingbathymetry and the associated ocean state (includi"ng wave, if applicable, and circulationpredictions) so that it can be applied with numerical model predictions of various character""isticsappropriate to USRS DRI sites (i.e. using the terrain-following FVCOM, or a multi-nest ROMSconfiguration).2. Apply the DA m""ethodology at various sites with the objective of estimating bathymetry usingobservations from satellite-, ship-, or land-based dat""a sources, with an emphasis on interpretingremote sensing observations and providing information that would be useful for the acous""ticalcharacterization of the region of interest.3. Utilize the DA methodology for ocean state estimation at Connecticut River, CT,"" Hood Canal,WA, and at the remaining USRS DRI sites. Starting with the observations at Hood Canal, weanticipate the availability o"f SWIFT drifter observations in addition to the suite of observationsfrom the first (CT River) experiment.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 20, 2017
- Source ID
- N000141812071
Entities
People
- Tuba Özkan-Haller
Organizations
- Office of Naval Research
- Oregon State University
- United States Navy