Bruce Parker

Optimal estimation of tidal open boundary conditions using predicted tides and adjoint data assimilation technique

Abstract Lateral tidal open boundary conditions which force tides in the internal region are estimated by an adjoint data assimilation system which assimilates predicted coastal tidal elevations into a two-dimensional Princeton Ocean Model for the East Coast of the United States. Control variables are the harmonic constants (amplitude and phase) of tidal constituents (M 2 , S 2 , N 2 , K 1 , O 1 ) along the open boundary. The cost function is defined by the difference between predicted and model-simulated tidal elevations at coastal tide gauge locations. The limited memory Broyden–Fletcher–Goldfarb–Shanno quasi-Newton method for large-scale optimization is implemented to minimize the cost function. Identical twin experiments are performed to verify the adjoint model and to examine sensitivity of model results to the number and spatial distribution of tide gauge stations. The results from the predicted tidal elevation assimilation experiments show that the simulated tidal elevations forced by the optimal open boundary conditions are more accurate than those forced by the open boundary conditions derived from Schwiderskis global tidal model. For M2 constituent, the maximum RMS error at tide gauge stations with data assimilation is generally 14 cm and the minimum correlation coefficient is 0.96. For the nine open coastal stations, the RMS errors are less than 5 cm . The results from the experiment in which five tidal constituents are considered together show that the RMS errors at the nine open coastal stations are less than 7 cm , and the correlation coefficients are greater than 0.99.

The tide predictions for D-Day

Based on the physics of Newton and Laplace, the big brass tide-predicting machine designed by Lord Kelvin was crucial for the success of the Normandy invasion in World War II.

Monitoring and modeling of coastal waters in support of environmental preservation

The improved monitoring and modeling capability resulting from recent technological advances in oceanographic sensors, computer processing power, and telecommunications can play a major role in environmental preservation. In particular, this capability can help improve: safe navigation and thus the prevention of maritime accidents that lead to hazardous spills; the effective cleanup of hazardous spills when they do occur; the real-time assessment of water quality problems; the assessment of long-term trends and variability due to both anthropogenic and climate change effects; and the understanding of key physical, chemical, and ecological processes.

Real-time oceanographic model systems: Present and future applications

Recent developments in instrumentation, telecommunication, and computer technologies, combined with advanced numerical modeling and forecasting techniques, now provide a capability for disseminating accurate forecasts of oceanographic parameters to a growing maritime user community. Real-time measurements can: (1) provide immediate oceanographic information to the user; (2) form the basis for more accurate forecasts; and (3) drive numerical hydrodynamic models to provide even broader marine information services. For the commercial shipping industry, real-time model systems represent an important step beyond reliance on classical tide predictions; making maximum use of available channel depths leads to safer and more economical commerce. Real-time/ forecast circulation will make navigation safer at key locations, and will increase the success of search and rescue operations and the clean-up of oil spills and other hazardous materials. Real-time dynamical model forecasting itself represents an important interpretative physical tool which can increase our understanding of the geophysical phenomena that affect the maritime community everyday. Uses for sophisticated real-time model systems, like uses for satellite imagery, will continue to develop.