Oceanic whitecaps (hereafter, W) or the characteristic whiteness of the sea foam is an important feature for predicting exchange of gases, sea spray aerosols (SSAs), heat and momentum transfer between the ocean and the atmosphere at the air-sea interface. Due to its increased surface emission and brightness temperature, whitecaps are critical for satellite retrievals of ocean albedo, ocean color, ocean surface wind vectors from satellite borne radiometer and microwave instruments. Most of the existing models predict W using wind speed and sea surface temperature (SST). However, numerous publications have pointed out that there are large uncertainties in the predicted W and using parameterizations based on wind-wave state can improve the precision of the predicted W. Here, we integrate the University of Miami Wave Model - 2.0 (UMWM) in Goddard Earth Observing System (GEOS) and use wave diagnostics to predict W. We choose the year 2006 for our global UMWM/GEOS runs because of the availability of W dataset from satellite observations. We run UMWM/GEOS at 0.5o x 0.5o by replaying to MERRA2 meteorology and evaluate the wave diagnostics using measurements from fixed buoys and satellite altimeters. We use three different parameterizations for W based on: 1) Reynolds number, 2) wave dissipation energy, and 3) volume of air entrained by breaking waves. We compare our results of W with previous studies and also with the satellite based observational dataset. Predicting W is important for understanding the processes at the air-sea interface. Therefore, this work is a step further in improving the uncertainties in the aerosol and atmospheric chemistry modules of the global models.
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