Improving The Sea Surface Wind Retrieval Algorithm For NASA Scatterometers Using Atmospheric Boundary Layer Models

The use of an atmospheric boundary layer (ABL) model is investigated to improve wind retrieval algorithms for NASA scatterometer projects. The ambiguity in wind direction retrieved from scatterometer measurements is removed with the aid of physical directional information obtained from the ABL model. This approach is based on the observation that sea level pressure is scalar and its field is more coherent than the corresponding wind field, and also that the measurement errors of sea level pressure are small compared with those of the retrieved wind vectors. A wind field obtained from the scatterometer measurements is first used to derive a pressure field by using an ABL model. After properly filtering smallscale noise in the derived pressure field, the wind field is retrieved by using an inverted ABL model. This derived wind information is then used to remove wind vector ambiguities. It is found that the ambiguity removal skill can be improved when the new scheme is used properly in conjunction with the median filter adopted for the scatterometer wind dealiasing. Moreover, it is believed that the new methodology will mitigate the dependency of the wind processing algorithm on external inputs, i.e., products of numerical weather prediction systems, which reveal deficiencies in accurately resolving some smaller scale and/or sporadic atmospheric phenomena.