HR: 14:40h
AN: OS53A-03 [Abstracts]
TI: Adjoint Data Assimilative Model Study of the Gulf of Maine Coastal Circulation
AU: * He, R
EM: ruoying@whoi.edu
AF: Woods Hole Oceanographic Institution, 98 Water Street, Woods Hole, MA 02543
United States
AU: McGillicuddy, D J
EM: dmcgillicuddy@whoi.edu
AF: Woods Hole Oceanographic Institution, 98 Water Street, Woods Hole, MA 02543
United States
AU: Lynch, D R
EM: daniel.lynch@dartmouth.edu
AF: Dartmouth College, Thayer School of Engineering, Hanover, NH 03755
United States
AB:
Data assimilation (DA) in the coastal ocean can be divided into category of either sequential estimation or variational
adjoint. Sequential estimation techniques blend models with observations directly, using a variety of algorithms with which
the relative weights of data and model are calculated. Variational adjoint techniques infer model control variables (e.g.
parameters, forcing functions, boundary conditions, etc.) that minimize the misfit between observations and predictions. The
advantage of the latter techniques over the former is that the resulting model solutions obey model dynamics.
In this study, the Gulf of Maine coastal circulation and the material property transport are investigated with the Dartmouth
variational adjoint DA modeling system, which assimilates in-situ data via inversion for the unknown sea level elevation at
open boundaries. In-situ observations include ADCP currents and coastal sea levels. The adjoint DA model skill is evaluated
by the inter-comparisons between modeled and observed drifter trajectories. Excellent model skill is found, demonstrating the
utility and effectiveness of the adjoint DA modeling system in bridging in-situ observations with coastal ocean model
simulations. Implications of the adjoint DA strategy on the emergent coastal ocean observing systems are discussed.
DE: 3337 Numerical modeling and data assimilation
DE: 4200 OCEANOGRAPHY: GENERAL
DE: 4219 Continental shelf processes
DE: 4255 Numerical modeling
SC: Ocean Sciences [OS]
MN: 2004 AGU Fall Meeting