HIGH RESOLUTION COASTAL CIRCULATION: MERGING MODELS AND OCEAN COLOR DATA*

摘要

Remotely-sensed ocean color provides a window into coupled biogeophysical dynamics at the surface of the coastal ocean. Satellite imagery provides synoptic, real-time measurements over large spatial scales; however, typical spatial resolution (250m – 1km) may be limiting when considering some coastal processes that evolve over much finer spatial scales (such as ~10m’s) . Futhermore, temporal resolution is generally lacking in remote sensing imagery with approximately one or two passes per day in comparison to coastal processes which occur on hourly (or less) scales. Thus, the underlying physical processes that influence the observed optical distributions are often too complex and are manifest at space and time scales that preclude full understanding from imagery alone. Alternatively, advanced numerical models of the coastal ocean applied at spatial scales of 10 to 100 m incorporate relevant coastal dynamics (such as wind, tide, and river forcing, vertical mixing, advection and dispersion), complex shorelines and bathymetry, and are able to predict coastal circulation over very short time scales throughout the entire water column. These high-resolution models are often exercised as a virtual laboratory for understanding the cause and effect between forcing and circulation. When coupled, numerical models and remotelysensed observations can provide a powerful tool to both understand and predict dynamical processes and optical patterns in coastal waters. From a military perspective, remotely-sensed ocean color data is often the only observational window on ocean processes in denied areas making the coupling of satellite imagery with numerical models all the more imperative for developing a preditive capability in such regions. Aside from a deepened understanding of coastal processes, merging numerically modeled circulation with satellite imagery can result in improvements to the modeled circulation, particularly in intertidal regions where few observations are available to quantify the land-sea interface. Once a more complete understanding of how ocean color data and modeled circulation are coupled, an appropriate data assimilation approach can be developed that will allow coastal ocean models to take full advantage of the observational information presented in the satellite imagery. SeaWIFS and MODIS satellites provide daily products of the bio-optical and SST properties for characterizing and monitoring coastal conditions (Arnone and Parsons, 2004). Advances in inter-satellite calibration and atmospheric correction have been used to provide quantitative analyses of the optical properties in coastal areas. These satellites can now be used to determine how optical characterisitics change from image to image; they provide a quantitative means for defining changes which can result from the physical forcing. Current algorithms used with these ocean color satellites are based on semianaytical approaches which use spectral changes to uncouple the inherent optical properies of absorption (total, phytoplanton, detritus and Colored dissolved organic) and backscatteirng (Lee et al. 2002). The backscattering properties are strongly associated with the particle concentration (in addition to the size , shape, index of refraction). Additionally, optical propeites such as the beam attenuation coefficient?