A method for routinely generating microwave surface emittance over land from coincident microwave and infrared satellite data has been developed. The method includes a surface skin temperature retrieval, and a dynamic cloud discrimination method, in addition to an explicit atmospheric correction based on in situ atmospheric sounding information. An example of results from the method are presented for a 70-day period over the central United States. Atmospheric-corrected microwave surface emittance results are shown to enhance the use of the microwave data sets for determining land surface characteristics, especially in regards to analysis of the data's frequency dependencies. Several problems that affect the use of the microwave brightness temperature data were examined, including natural characteristics of the spatial and temporal variability of the microwave background signature. The microwave surface emittance was found to be sensitive to numerous rain events captured in the data set. Application of this method to generate longer-term climatologies of microwave surface emittance should improve the understanding of the microwave surface emittance behavior. In particular, realistic spatial distributions of microwave surface emittance should enhance current atmospheric microwave remote sensing efforts over land. The microwave surface emittance data set also shows potential in nonforested regions for flood-monitoring purposes using change detection methods.