Document Type
Article
Publication Date
6-1998
DOI
10.1029/98jc00797
Publication Title
Journal of Geographical Research
Volume
103
Issue
C6
Pages
12761-12782
Abstract
Dynamical assimilation of surface elevation from tide gauges is investigated to estimate the bottom drag coefficient and surface stress as a first step in improving modeled tidal and wind-driven circulation in the Chesapeake Bay. A two-dimensional shallow water model and an adjoint variational method with a limited memory quasi-Newton optimization algorithm are used to achieve this goal. Assimilation of tide gauge observations from 10 permanent stations in the Bay and use of a two-dimensional model adequately estimate the bottom drag coefficient, wind stress, and surface elevation at the Bay mouth. Subsequent use of these estimates in the circulation model considerably improves the modeled surface elevation in the entire Bay. Assimilation of predicted tidal elevations yields a drag coefficient, defined in the hydraulic way, varying between 2.5 x 10(-4) and 3.1 x 10(-3) The bottom drag coefficient displays a periodicity corresponding to the spring-neap tide cycle with a maximum value during neap tide and a minimum value during spring tide. From assimilation of actual tide gauge observations, it is found that the fortnightly modulation is altered during frontal passage. Furthermore, the response of the sea surface to the wind forcing is found to be more important in the lower Bay than in the upper Bay, where the barometric pressure effect seems to be more important.
Original Publication Citation
Spitz, Y.H., & Klinck, J.M. (1998). Estimate of bottom and surface stress during a spring-neap tide cycle by dynamical assimilation of tide gauge observations in the Chesapeake Bay. Journal of Geophysical Research, 103(C6), 12761-12782. doi: 10.1029/98jc00797
Repository Citation
Spitz, Y. H. and Klinck, J. M., "Estimate of Bottom and Surface Stress During a Spring-Neap Tide Cycle by Dynamical Assimilation of Tide Gauge Observatons in the Chesapeake Bay" (1998). CCPO Publications. 60.
https://digitalcommons.odu.edu/ccpo_pubs/60