Monday, 15 August 2016
Grand Terrace (Monona Terrace Community and Convention Center)
Many air-sea interaction processes are quantified in terms of whitecap fraction W because oceanic whitecaps are the most visible and direct way of observing breaking of wind waves in the open ocean. Enhanced by breaking waves, surface fluxes of momentum, heat, and mass are critical for ocean-atmosphere coupling and thus affect the accuracy of models used to forecast weather, predict storm intensification, and study climate change. Whitecap fraction has been traditionally measured by extracting the high-intensity pixels marking white water in still photographs or video images collected from towers, ships, and aircrafts. Satellite-based passive remote sensing of whitecap fraction is a recent development that allows long term, consistent observations of whitecapping on a global scale. The remote sensing method relies on changes of ocean surface emissivity at microwave frequencies (e.g., 6 to 37 GHz) due to presence of sea foam on a rough sea surface. These changes at the ocean surface are observed from the satellite as brightness temperature TB. A year-long W database built with this algorithm has proven useful in analyzing and quantifying the variability of W, as well as estimating fluxes of CO2 and sea spray production. The algorithm to obtain W from satellite observations of TB was developed at the Naval Research Laboratory within the framework of WindSat mission. The W(TB) algorithm estimates W by minimizing the differences between measured and modeled TB data. The Radiative Transfer Equation (RTE) is used to formulate a geophysical model function (GMF) to calculate TB at the top of the atmosphere as contributions from the atmosphere and the ocean surface. The ocean surface emissivity combines the emissivity of rough sea surface and the emissivity of areas covered with foam. Wind speed U10 and direction φ, sea surface temperature T, water vapor V, and cloud liquid water L are required inputs to the atmospheric, roughness and foam models comprising the GMF. The W(TB) algorithm has been recently updated to use new sources and products for the input variables. In this poster, we present new version of the W(TB) algorithm that uses updated GMF. We combine the latest WindSat GMF (version 2.4) for the atmosphere and surface emissivity with our radiative transfer model for foam with vertical void fraction profile. We describe the new GMF, present new results for whitecap fraction W, and analyze differences between the new W data and those obtained with the previous GMF.
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