Assessment of the U.S. Outer Continental Shelf Environmental by Commission on Life Sciences Staff

By Commission on Life Sciences Staff

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Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. INTRODUCTION 19 WHY MMS NEEDS PHYSICAL OCEANOGRAPHIC INFORMATION Physical oceanography provides important inputs for calculating estimates of the transport and fate of oil and related materials in the ocean.

The OSRA model estimates the probability of oil spills in a specific lease area, calculates oil-spill trajectories from selected launch points, and estimates the probability that an environmental resource or coastline segment will be contacted by releases from the selected launch points. It provides the quantitative basis for calculating the probability of occurrence of an oil spill combined with the probability that a given spill will come into contact with resources. Physical oceanographic support of OSRA modeling has been provided directly through numerical modeling studies of the circulation of each of the major OCS regions—the outputs of the circulation models are "data" for OSRA models—and indirectly in the form of extensive data bases obtained through large-scale field observation programs.

Incorporation of higher-frequency variations (tides, Ekman transport, slope currents, eddy/ring dynamics) in the flow are either ignored as being unimportant or are parameterized in the OSRA model. The OSRA model uses a Monte Carlo technique to calculate spill trajectories for selected launch points in a proposed lease area by season or month. The model then predicts (1) the probability of oil-spill occurrence using historical data, (2) the "hits" or number of times a spill encounters an environmental resource target (wildlife, fishing area, rookery, spawning area, nesting area, and so on) or shoreline segments, and (3) the probabilities of conditional impact probabilities on the resource within a preselected time.

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