Coastal Processes and Hazards in the Southern California Bight Using Multiple Satellite Sensors
Benjamin Holt(1) and Paul DiGiacomo(1)
Jet Propulsion Laboratory,
4800 Oak Grove Drive,
Pasadena, CA 91109,
As part of ongoing interdisciplinary studies, we seek to provide a better understanding of the complex physical, ecological and biogeochemical processes in the coastal waters off southern California. At local and event-scales, this coastal area is characterized by phenomena such as eddies, internal waves and dust storms. At basin and climate scales, this region is impacted by the California Current (the eastern boundary current of the North Pacific) and remote forcing associated with ENSO events that strongly alter wind, current, water mass, and precipitation patterns. Furthermore, the Southern California Bight is adjacent to one of the largest industrialized urban populations in the world, which results in significant anthropogenic inputs to the coastal marine ecosystem, including such pollution hazard concerns as storm/waste-water runoff and oil spills. To address these diverse issues, we utilize a variety of satellite data including high-resolution ocean color observations (e.g., SeaWiFS, MODIS, and MERIS), sea surface temperature measurements (e.g., AVHRR, MODIS, and AATSR), and Synthetic Aperture Radar (SAR) imagery of surface features and derived wind fields (e.g., RADARSAT, ERS, and ASAR) that are complemented and validated by coincident field data (from moorings, drifters, ships, and shore-based HF radar) and more recently, a nested coastal current model. These synergistic data sets enable the detection, quantification and understanding of under-sampled and poorly described coastal ocean processes and pollution hazards of the type described above and an assessment of their ecological (e.g., harmful algal blooms), biogeochemical (carbon cycling), and human (pathogens) impact. We will present an overview of representative case studies on the observation of these processes and hazards that demonstrate the utility of multiple sensors.