摘要：During the Global Ocean Data Assimilation Experiment (GODAE), numerical modeling and prediction in coastal and shelf seas benefited from development of state-of-the-art, data-assimilative, and data-validated large-scale models that can supply initial and boundary conditions to nested domains. Rather than attempting an exhaustive synthesis, this article illustrates the progress in coastal ocean modeling and prediction made possible by GODAE, either directly by providing estimates, or more subtly by rendering coastal forecasting more feasible and its applications more obvious.
