Spatially adaptive ocean surface wind retrievals using satellite microwave scatterometer measurements over tropical cyclones

An algorithm is presented which extends the capabilities of the NASA Scatterometer (NSCAT) Wind Retrieval Algorithm to include retrievals using 25 km wind vector cells (SARA-25) and individual normalized radar cross section measurement cells (SARA-max). This Spatially Adaptive Retrieval Algorithm (SARA) can retrieve very high resolution and precise tropical cyclone wind fields when using a model wind field with ideal (no noise, perfect model function) measurements. It is shown that the actual SARA-25 retrievals are very close to the 50 km NSCAT retrievals for a wide range of wind speeds and directions. The benefit from SARA is in cases where higher sampling is needed to fully describe the wind field. Regions such as the eyewall of a tropical cyclone where, measurements of peak winds are a high priority, are well suited for SARA analysis. Using only one measurement for a retrieval in an eyewall. eliminates the effects of averaging used in SARA-25 and 50 km sampling. The SARA also provides a means to test if adjacent measurements are similar to each other. Dissimilar measurements are most likely due to the effects of rain. Hence SARA provides a means to evaluate which cells are affected by rain.