There is a natural correspondence between soil moisture and precipitation. Precipitation is a source for soil moisture. Soil moisture represents memory effects for precipitation and controls the partitioning of precipitation into infiltration, surface runoff, and evaporation/transpiration from land surfaces. It also controls the microwave emission background that impacts the physically-based precipitation. The GPM Microwave Imager (GMI) will provide more observations over mid/high latitude land areas than its predecessor TRMM. For precipitation algorithms, the underlying microwave surface emissivity is subject to wider variations immediately following rainfall events, and a strong correspondence should exist between the spatial distribution of emissivity and precipitation if the ground is not close to saturation. Since the emissivity at each radiometer channel is highly correlated, a multi-channel microwave land surface emissivity retrieval of land surface soil moisture, vegetation water content, and land surface temperature parameters is demonstrated. Our goal is to quantify the spatial and temporal variations of microwave emission background using environment variations in soil moisture and vegetation water content. The land surface retrievals of these parameters are based on a multi-channel maximum-likelihood algorithm using 10 to 37 GHz passive microwave channels. The algorithm outputs were validated against multi-scale data including soil moisture climatology, ground in-situ network data, precipitation patterns, and vegetation data from AVHRR sensors. Examples are shown for cases that are further subsetted by the presence and amount of previous-time precipitation.