Interdisciplinary coastal observations over a two-week period in the northern Gulf of Mexico reveal a complex and dynamic bottom boundary layer (BBL) that is characterized by both biological and suspended sediment (biogeo-) optical signals. Much of the BBL optical variance is concealed from remote sensing by the opacity of the nearly omnipresent surface river plume, however, the BBL physical dynamics and resulting optical excitation are indeed responding to surface wind stress forcing and surface gravity wave-induced turbulence. Here we present a series of numerical modeling efforts and approaches aimed towards resolving and simulating these observed biogeo-physical and –optical processes. First, we examine results from the Tactical Ocean Data System (TODS), which combines daily satellite imagery with numerical circulation model results to render a three-dimensional estimate of the optical field and then execute a reduced-order complexity advection-diffusionreaction model to render hourly forecasts. Whereas the TODS system has the advantage of effectively assimilating both glider data and satellite images, the 3D generation algorithms still have difficulty in the northern Gulf’s complex 3-layered system (surface plume, geostrophic interior, BBL). Second, we present results from the Coupled Ocean-Atmosphere Prediction (COAMPS) system that has been modified to include interactive surface-gravity wave simulations. Results from this complex numerical modeling system suggest that Stokes drift current (SDC) has a potentially major role in determining the physical and kinematic characteristics of the BBL, and will substantially impact model-based estimates of sediment resuspension and transport.
Jason K. Jolliff, Sherwin Ladner, Travis Smith, Allison Penko, Ewa Jarosz, and Todd Lovitt, "Simulating biogeo-optical dynamics in the bottom boundary layer: northern Gulf of Mexico test case," Proc. SPIE 10186, Ocean Sensing and Monitoring IX, 101860S (Presented at SPIE Defense + Security: April 12, 2017; Published: 22 May 2017); https://doi.org/10.1117/12.2263644.
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