The Tropical Rainfall Measuring Mission (TRMM) was launched in November of 1997. TRMM Microwave Imager (TMI) provides a least a daily coverage over the southern Continental US (up to 38N latitude). TMI is a dual-polarization passive microwave conical scanning radiometer operating at 10.65, 19.4, 21.3, 37.0 and 85.5 GHz. It has a spatial resolution of about 40-km at 10.65 GHz. The goal of this project is to develop a soil moisture pathfinder data set using the TMI observations. TMI provides multiple orbits over the southern US at varying times of observation. Methods to adjust for diurnal changes associated with this temporal variability and how to mosaic these orbits are required. The algorithm for deriving soil moisture and temperature from TMI observations is based on a physical model of microwave emission from a layered soil-vegetation-atmosphere medium. Dual polarization observations at 10.65 GHz are used in the retrieval. The land surface is modeled as an absorbing vegetation layer above soil. An iterative, least-squares-minimization method is employed in the retrieval algorithm. Retrieved variables represent area-averages over the 10.65 GHz footprints and also averages over the vertical sampling depth in the soil/vegetation medium. As the vegetation cover increases, the retrieval error increases. Uncertainties associated with land surface parameters (such as soil roughness, vegetation scattering and opacity coefficient, soil texture, etc.) propagate into the retrieval uncertainties for soil moisture and temperature. Validation to date has focused on data collected in field campaigns with ground measurements over the US Southern Great Plains (SGP) in Oklahoma and the Little River Watershed, GA. During both the experiments, the region was dry at the onset of the experiment, and experienced moderate rainfall throughout the watershed during the course of the experiment. The watersheds experienced a dry-down before the end of the experiment. It is important to recognize that these high frequencies respond to a very shallow soil layer (~1-2 cm). Characterizing this layer is difficult and it can change rapidly. The significance of vegetation is very high at these higher frequencies. Based upon further validation and algorithm development, a five year daily soil moisture data set for applicable regions of the southern U.S. will be produced.