In this two-part study, a single-Doppler parameter retrieval technique is developed and applied to a real-data case to provide initial conditions for a short-range prediction of a supercell thunderstorm. The technique consists of the sequential application of a single-Doppler velocity retrieval (SDVR), followed by a variational velocity adjustment, a thermodynamic retrieval, and a moisture specification step. By utilizing a sequence of retrievals in this manner, some of the difficulties associated with full-model adjoints (possible solution nonuniqueness and large computational expense) can be circumvented. In Part I, the SDVR procedure and present results from its application to a deep-convective storm are discussed. Part II focuses on the thermodynamic retrieval and subsequent numerical prediction. For the SDVR, Shapiro's reflectivity conservation-based method is adapted by applying it in a moving reference frame. Verification of the retrieved wind fields against corresponding dual-Doppler analyses indicates that the best skill scores are obtained for a reference frame moving with the mean wind, which effectively reduces the problem to a perturbation retrieval. A decomposition of the retrieved wind field into mean and perturbation components shows that the mean wind accounts for a substantial portion of the total retrieved azimuthal velocity. At low levels, where the retrieval skill scores are especially good, the retrieved perturbation azimuthal velocity is mostly associated with the polar component of vorticity. Missing from the retrieved fields (compared to the dual-Doppler analysis) is most of the low-level azimuthal convergence. Consistent with this result, most of the retrieved updraft is associated with convergence of the perturbation radial velocity, which is calculated from the observed radial velocity and directly used in the wind retrieval.