Wednesday, 20 April 2016: 2:30 PM
Ponce de Leon B (The Condado Hilton Plaza)
Tropical cyclones are regions of very strong rain and very high winds, both of which present a major challenge to surface wind vector retrieval from Ku-band scatterometers. Newly developed neural-net-based geophysical model functions are capable of retrieving wind speed in tropical cyclones. However, in order to study inflow, accurate estimates of the surface wind direction are needed. Drop sonde wind profiles are inherently single realizations in a strongly turbulent flow. However, drop sonde surface pressure is an inherently mean flow property. We are developing a methodology for determining the surface wind directions that makes use of the surface pressure measurements and our methodologies for retrieving surface pressure fields from satellite ocean surface wind vector data. We invert this methodology to seek the optimal wind directions that provide the best match between derived and observed surface pressures. A by-product of this analysis is a satellite estimate of the irrotational and divergence-free deformational field around the tropical cyclone. We are investigating how best to use this calculation as part of our wind direction validation.
- Indicates paper has been withdrawn from meeting
- Submission entered in competition