Precipitation is a dominating quantity in microwave radiometry. The large emission and scattering signals of rain and ice, respectively, introduce large contributions to the measured brightness temperature. While this allows for accurate sensing of precipitation, it also results in degraded performance when retrieving other geophysical parameters, such as near-surface ocean winds. In particular, the retrieval of wind direction requires precise knowledge of polarization, and nonspherical particles can result in a change in the polarization of incident radiation. The aim of this dissertation is to investigate the polarizing effects of precipitation in the atmosphere, including the existence of a precipitation signal in the third Stokes parameter, and compare these effects with the current sensitivities of passive wind vector retrieval algorithms. Realistic simulated precipitation profiles give hydrometeor water contents which are input into a vector radiative transfer model. Brightness temperatures are produced within the model using a reverse Monte Carlo method. Results are produced at three frequencies of interest to microwave polarimetry, 10.7 GHz, 18.7 GHz, and 37.0 GHz, for the first 3 components of the Stokes vector.