The quality of the retrieved wind vectors from satellite imagery has undergone dramatic improvement in recent years. In addition to the classical cloud track winds, additional coverage is now being provided outside the cloudy regions through the tracking of clear-sky water vapor features. One of the long-standing problems in the use of satellite winds based on feature tracking is how to correctly determine the height (or pressure) for which a particular wind vector is representative. This is true for all tracking winds, but especially so for the clear-sky water vapor winds. Currently, this so-called height assignment is in principle done externally to the data assimilation system for which the observations are ultimately targeted. At NASA’s Data Assimilation Office (DAO), a series of experiments have been carried out in which this first-guess height is modified interactively by the data assimilation system itself in order to minimize a cost function penalizing the difference between the observed and predicted wind and temperature, as well as the total adjustment allowed. The initial results indicate that an interactive height assignment algorithm may further improve the analysis impact from satellite winds.