An algorithm is developed to retrieve sea surface wind vectors from satellite microwave polarimetry. The radiative transfer model produces simulated measurements under global atmospheric and surface conditions. The simulations for wind speeds less than 5 m s−1 are not utilized in the retrievals because of the unreliable performance of the current surface emissivity model. In the algorithm, the upwelling and downwelling radiative components are treated as one variable since the two components are highly correlated. As a result, under rain-free conditions, the full polarimtric measurements obtained at a single frequency can form a closure of a set of radiative transfer equations so that both surface and atmospheric column parameters can be simultaneously derived. The first guess to the solutions is normally required because the retrieval is nonlinear. In doing so, the third and fourth Stokes components and their ratio are utilized to estimate the wind direction. It is found that this ratio alone can determine the wind direction with an accuracy of 30 degrees. Without the sensor noises being added to the simulations, the algorithm can produce the wind direction with an RMS error of 6.5 degrees and the wind speed with an error of 0.3 m s−1, respectively. If the realistic random noises are taken into account with 0.1 K for vertical and horizontal polarizations and 0.15 K for the third and fourth Stokes components, the errors increase to about 10 degrees and 0.6 m s−1 for the wind direction and speed, respectively. This wind speed error is much smaller than that from the statistical algorithms (1.4 m s−1) applied for the same data set. Thus the physical retrieval significantly improves the uses of the microwave polarimetric data for remote sensing of ocean wind.