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High-resolution passive polarimetric microwave mapping of ocean surface wind vector fields

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2 Author(s)
Piepmeier, J.R. ; Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA ; Gasiewski, A.J.

The retrieval of ocean surface wind fields in both one and two dimensions is demonstrated using passive polarimetric microwave imagery obtained from a conical-scanning airborne polarimeter. The retrieval method is based on an empirical geophysical model function (GMF) for ocean surface thermal emission and an adaptive maximum likelihood (ML) wind vector estimator. Data for the GMF were obtained using the polarimetric scanning radiometer/digital (PSR/D) on the NASA P-3 aircraft during the Labrador Sea Deep Convection Experiment in 1997. To develop the GMF, a number of buoy overflights and GPS dropsondes were used, out of which a GMF of 10.7, 18.7, and 37.0 GHz azimuthal harmonics for the first three Stokes parameters was constructed for the SSM/I incident angle of 53.1°. The data show repeatable azimuthal harmonic coefficient amplitudes of ~2-3 K peak-to-peak, with a 100% increase in harmonic amplitudes as the frequency is increased from 10.7 to 37 GHz. The GMF is consistent with and extends the results of two independent studies of SSM/I data and also provides a model for the third Stokes parameter over wind speeds up to 20 m/s. The aircraft data show that the polarimetric channels are much less susceptible to geophysical noise associated with maritime convection than the first two Stokes parameters. The polarimetric measurement technique used in the PSR/D also demonstrates the viability of digital correlation radiometry for aircraft or satellite measurements of the full Stokes vector. The ML retrieval algorithm incorporates the additional information on wind direction available from multiple looks and polarimetric channels in a straightforward manner and accommodates the reduced SNRs of the first two Stokes parameters in the presence of convection by weighting these channels by their inverse SNR

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:39 ,  Issue: 3 )