HR: 0800h
AN: OS21C-1274    [Abstracts]
TI: Characterizing Submesoscale Ocean Color Variability in the Sargasso Sea in the Vicinity of the Bermuda Atlantic Time-series Site (BATS): A Geostatistical Approach
AU: * Wallis, A
EM: alise.wallis@verizon.net
AF: Woods Hole Oceanographic Inst., Dept. Marine Chem & Geochem Mail Stop 25, Woods Hole, MA 02543 United States
AU: Doney, S C
EM: sdoney@whoi.edu
AF: Woods Hole Oceanographic Inst., Dept. Marine Chem & Geochem Mail Stop 25, Woods Hole, MA 02543 United States
AU: Glover, D M
EM: dglover@whoi.edu
AF: Woods Hole Oceanographic Inst., Dept. Marine Chem & Geochem Mail Stop 25, Woods Hole, MA 02543 United States
AU: Nelson, N
EM: norm@icess.ucsb.edu
AF: ICESS, Univ. Calif. Santa Barbara, Santa Barbara, CA 93106 United States
AB: Using the geostatistical method of semivariogram analysis, high resolution SeaWiFS imagery (1.1 km) is analyzed to determine ocean color variability on the submesoscale (1 - 10 km). Numerous studies have demonstrated the importance of mesoscale (10 km - 200 km) nutrient upwelling in structuring and fueling ocean productivity in oligotrophic environments; modeling experiments suggest further enhancements of productivity due to submesoscale physics. Our study area, the Sargasso Sea surrounding Bermuda, is selected based on an earlier study of global mesoscale ocean color semivariance that shows moderate levels of mesoscale variability and a high level of unresolved variability. A time-series of data is analyzed, and one- and two-dimensional semivariograms are produced for each month. Based on these semi-variograms, we demonstrate that much of the previously unresolved variability is indeed caused by submesoscale structures and that submesoscale and mesoscale variability are comparable in magnitude. Anisotropy on local scales, $\sim$10-20 km, is observed based upon semivariograms computed from 20 km$^{2}$ subsamples of single day images, showing that much of the submesoscale signature is occurring in elongated filaments. Unresolved submesoscale variability may be non-geophysical noise (instrument, aerosols, algorithms {\em etc.}) as well as variability on an even finer scale.
DE: 4806 Carbon cycling
DE: 4855 Plankton
DE: 4275 Remote sensing and electromagnetic processes (0689)
DE: 4568 Turbulence, diffusion, and mixing processes
SC: Ocean Sciences [OS]
MN: 2004 AGU Fall Meeting