Improving Ku-band Scatterometer Ocean Surface Wind Direction Retrievals in Tropical Cyclones

Abstract:

Tropical cyclones are regions of very strong rain and very high winds, both of which present major challenges to surface wind vector retrieval from Ku-band scatterometers. Wind speed and wind direction retrievals can incur severe errors in regions of high rain rates. One particular signature of rain contamination is wind directions in the across-swath direction, which often leads to displaced circulation centers. Recently, Stiles et al. (2014) developed a method for retrieving QuikSCAT tropical cyclone wind speeds using a neural network approach that was tuned using H*WIND surface wind analyses and passive microwave-estimated rain rates from satellites. We are developing a scene-wide methodology by which a set of dynamically-consistent wind directions can be estimated from these wind speeds. The method is based on an iterative use of a tropical cyclone-specific sea-level pressure retrieval technique that we developed. The sea-level pressure analysis uses a boundary layer model that includes the dynamical shallowing of the tropical cyclone boundary layer toward the storm center, a roll-off in surface drag at high wind speeds, and, storm motion-corrected nonlinear mean flow advection effects. Scene-wide consistency is enforced by the integral nature (with respect to the surface wind vector field) of the derived surface pressure pattern and a constraint that the geostrophic contribution to the total flow is non-divergent. We are currently developing methods to evaluate the retrieved wind directions based on HRD aircraft observations and a limited-domain wind vector partitioning of the retrieved wind vectors into irrotational, non-divergent, and, background flow deformation contributions.