In the context of continuing development and implementation of global and regional ocean observing systems, we describe here the need and essential ingredients for a coastal ocean forecasting system focused on sea level and associated inundation issues and applications. Such a system
must consist of the following key components: 1) satellite and in situ observations, 2) atmospheric forcing, 3) ocean circulation and tide modeling, 4) data assimilation for initialization, 5) forecast error estimation, and 6) data and model management. We describe these components,
their continuing development and integrated implementation and application as part of a prototype coastal ocean forecast system for the U.S. West Coast. The multiscale nested modeling approach utilized here has demonstrated that sea level simulation can be improved by increasing the spatial
resolution of observations. This and other regional ocean forecast systems are complementary and necessary elements of the emerging Global Ocean Observing System (GOOS) needed to predict changes in sea level. Building on the increasing maturity of ocean observing and forecasting capabilities,
there are a number of significant challenges that require immediate attention, planning and development. These include: 1) further development of models, data assimilation algorithms and information management system, 2) adaptive sampling to reduce uncertainty in ocean forecasting, 3) Observing
System Simulation Experiments (OSSE) to optimize observing system design, 4) bridging the land-sea boundary, and 5) moving from measurements to information in support of management and decision-making.
Development, implementation, and validation of a California coastal ocean modeling, data assimilation, and forecasting system
