Rapid Assessment of the Coastal Ocean Environment
203
itly by the almost incompressible and hydrostatic primitive equations (CushmanRoisin, 1994; Robinson, 1996). Spatial scales are lower bounded by several hundred meters and temporal scales, by a few hours. Phenomena include, e.g., currents, meanders, eddies, fronts, jet filaments, topographic and coastline effects,
surface and bottom boundary layers, upwelling, coastally trapped waves, barotropic and baroclinic tides. The effects of smaller scale and higher frequency physical
processes (e.g. turbulence, tidal mixing) are parameterized in the primitive equations and referred to as sub-grid scale processes in accord with the numerical representation of the dynamical model.
The ocean evolves in time, both as a direct response to external, surf ace and body
forces, and also via internal dynamical processes. The former include winds and
surface fluxes ofheat and fresh water. Where air-sea interactions are important, an
accurate meteorological forecast is needed for the ocean forecast. Oceanic internal
instabilities and resonances, which include the meanders of currents, frontogenesis,
eddying and wave propagation, are generally analogous to atmospheric weather
phenomena and are called the internal weather of the sea. The spatial scales of
important internal ocean weather phenomena range from 0(10 lan) (sub-mesoscale
or synoptical dynamical event scale) to 0(100 lan) (mesoscale or evolutionary
scale). These relatively short scales require ocean forecasts generally to be carried
out regionally rather than globally. The regional forecast problem then has additional forces appearing as fluxes through horizontal boundaries, representing both
larger scales of direct forcing, remote internal dynamical events and land-sea interactions in the littoral zone. The development of a regional forecast system and
capability depends both upon the scales and processes of direct interest and the
scales and processes that are dominant in the operational region and its surroundings. The forecast region or region of influence is often necessarily larger than the
region of operational interest.
The ocean is intermittent, eventful, and episodic, and ocean circulation is characterized by very many dynamical processes occurring over a broad range of nonlinearly interactive scales in space and time. Intermittencies and multiscales have led
to the concepts of adaptive sampling and nesting in ocean forecasting. Observations are used to initialize dynamical forecast models, and further observations are
continually assimilated into the models as the forecasts advance in time. Such
observations are generally difficult, costly and sparse. If a region of the ocean were
to be sampled uniformly over a predetermined space-time grid, adequate to resolve
scales of interest, only a small subset of those observations would have significant
impact on the accuracy of the forecasts. The impact sub set is related to intermittent
energetic synoptic dynamical events. For most of the energetic variability in the
ocean, the location and timing of such events is irregular and not a priori known.
However, a usefully ac curate forecast targets such events and forms the basis for
the design of a sampling scheme tailored to the ocean state to be observed. Sampling schemes can be determined subjectively by experience or objectively by minimizing a selected forecast error metric. Adaptive sampling is efficient, can
drastically reduce observational requirements, and is essential for effective REA.
203
itly by the almost incompressible and hydrostatic primitive equations (CushmanRoisin, 1994; Robinson, 1996). Spatial scales are lower bounded by several hundred meters and temporal scales, by a few hours. Phenomena include, e.g., currents, meanders, eddies, fronts, jet filaments, topographic and coastline effects,
surface and bottom boundary layers, upwelling, coastally trapped waves, barotropic and baroclinic tides. The effects of smaller scale and higher frequency physical
processes (e.g. turbulence, tidal mixing) are parameterized in the primitive equations and referred to as sub-grid scale processes in accord with the numerical representation of the dynamical model.
The ocean evolves in time, both as a direct response to external, surf ace and body
forces, and also via internal dynamical processes. The former include winds and
surface fluxes ofheat and fresh water. Where air-sea interactions are important, an
accurate meteorological forecast is needed for the ocean forecast. Oceanic internal
instabilities and resonances, which include the meanders of currents, frontogenesis,
eddying and wave propagation, are generally analogous to atmospheric weather
phenomena and are called the internal weather of the sea. The spatial scales of
important internal ocean weather phenomena range from 0(10 lan) (sub-mesoscale
or synoptical dynamical event scale) to 0(100 lan) (mesoscale or evolutionary
scale). These relatively short scales require ocean forecasts generally to be carried
out regionally rather than globally. The regional forecast problem then has additional forces appearing as fluxes through horizontal boundaries, representing both
larger scales of direct forcing, remote internal dynamical events and land-sea interactions in the littoral zone. The development of a regional forecast system and
capability depends both upon the scales and processes of direct interest and the
scales and processes that are dominant in the operational region and its surroundings. The forecast region or region of influence is often necessarily larger than the
region of operational interest.
The ocean is intermittent, eventful, and episodic, and ocean circulation is characterized by very many dynamical processes occurring over a broad range of nonlinearly interactive scales in space and time. Intermittencies and multiscales have led
to the concepts of adaptive sampling and nesting in ocean forecasting. Observations are used to initialize dynamical forecast models, and further observations are
continually assimilated into the models as the forecasts advance in time. Such
observations are generally difficult, costly and sparse. If a region of the ocean were
to be sampled uniformly over a predetermined space-time grid, adequate to resolve
scales of interest, only a small subset of those observations would have significant
impact on the accuracy of the forecasts. The impact sub set is related to intermittent
energetic synoptic dynamical events. For most of the energetic variability in the
ocean, the location and timing of such events is irregular and not a priori known.
However, a usefully ac curate forecast targets such events and forms the basis for
the design of a sampling scheme tailored to the ocean state to be observed. Sampling schemes can be determined subjectively by experience or objectively by minimizing a selected forecast error metric. Adaptive sampling is efficient, can
drastically reduce observational requirements, and is essential for effective REA.