On the retrieval of bubble properties from space lidar and their impact on acoustic transmission loss

Damien B Josset1, David W Wang2, Ivan B. Savelyev3, Magdalena D Anguelova4, Richard S. Keiffer5 and J Paquin Fabre5, (1)US Naval Research Laboratory, Washington, DC, United States, (2)U.S. Naval Research Laboratory, Ocean Sciences, Stennis Space Center, United States, (3)U. S. Naval Research Laboratory, Washington, United States, (4)Naval Research Lab, Washington, DC, United States, (5)US Naval Research Lab, Code 7180, Stennis Space Center, MS, United States
Abstract:
Quantifying the oceanic whitecaps and subsurface bubbles is critical to characterize the long term evolution of the ocean environment as they are the primary mechanism through which atmosphere and ocean exchange heat, momentum, and gas. Bubble bursting is a major production mechanisms for cloud condensation nuclei in the marine boundary layer (Quinn and Bates 2011). Turbulence driven exchange at the air-sea interface is associated with wave breaking and this includes bubble-mediated gas transfer (Woolf et al., 2007).

Additionally, in the presence of bubbles, acoustic propagation in the ocean surface mixed layer can be greatly diminished. A number of environmental parameters are critical to accurately model the acoustic Transmission Loss: the roughness of the surface, the depth of the sonic layer (related to the mixed layer), and the changes in sound velocity due to the bubbles (Fabre et al., 2009). The bubbles directly scatter acoustic energy and the rough surface modifies the angle of incidence which further increases downward scattering.

Present techniques for ocean remote sensing rely primarily on water leaving radiance and surface

properties (wind, surface salinity, sea surface temperature). Lidar is fundamentally different because visible light penetrates well into the water body and has the unique capability to provide a vertical profile of ocean properties.

In the past few years, we have demonstrated several applications of the ocean surface and subsurface signal from the space lidar onboard the CALIPSO satellite. We have shown that this signal included the unambiguous signature of surface and subsurface bubbles but this feature still has to be exploited. In this presentation, we will show results of whitecaps/bubble identification from the dual wavelength polarized space lidar return. We will present preliminary results of bubble properties quantification and discuss the use of these data as inputs of NRL acoustic propagation models.

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