Abstract   Estimating Antarctic Firn Average Emissivity Trends at the Ski Hi Automatic Weather Station Firn is compacted, near-surface snow enduring for more than one season not yet compressed into glacial ice. Knowledge of firn surface temperature trends across the Antarctic ice sheet is useful for documenting and quantifying change and providing a temporal and spatial context for research during the Antarctic International Polar Year (IPY). Satellite passive microwave radiometer data can provide surface temperature trend estimates across limited temporal and spatial gaps in Automatic Weather Station (AWS) coverage. Techniques to derive surface temperatures from passive microwave data have been pioneered by Jezek et al., (1993) and. Shuman et al., (1995). Using the methods of previous researchers, the Summer 2006 Undergraduate Research Experience (URE) Antarctic Temperature Mapping Team, is comparing archived surface temperature data from an AWS on the West Antarctic Ice Sheet with coincident daily brightness temperature data collected by the Special Sensor Microwave Imager (SSM/I) aboard the Defense Meteorology Satellite Program (DMSP) polar orbiting meteorology satellite series. The ratio of passive microwave brightness temperature and AWS in-situ near surface temperature provides the firn emissivity estimate necessary to extrapolate surface temperature trends across temporal and spatial gaps in either the AWS or SSM/I record. The relationship between emissivity and surface temperature is generally known as the ‘Rayleigh-Jeans Approximation’ (Hall and Martinec, 1985). The spatial and temporal variability of firn emissivity is not well understood but known to be much less variable than daily temperature. AWS temperatures at 3 hourly intervals for the “Ski Hi” AWS site (75º South Latitude, 71 º West Longitude) in West Antarctica were obtained from the AWS Project data archive at the University of Wisconsin’s Space Science and Engineering Center (SSEC). The passive microwave time-series of daily DMSP SSM/I brightness temperatures, geographically and temporally coincident with the Ski Hi site were obtained from Dr. Chris Shuman at NASA Goddard. Daily SSM/I brightness temperatures and corresponding Ski Hi AWS surface temperatures were tabulated in a Microsoft EXCEL spread sheet. The daily ratio of the SSM/I brightness temperature to the AWS surface temperature provided an emissivity trend from which to extrapolate surface temperatures The Ski Hi AWS operated from late February 1994 until late November 1998. The team will develop mathematical/statistical techniques to robustly estimate the surface emissivity trend at the Ski Hi site for the period January 1, 1995 through November, 1998, and use it to obtain a continuous estimate of surface temperature during data gaps in either the SSM/I or the AWS archive. Future work will establish emissivity trends at other AWS sites. These values will be combined with surface elevation data to extrapolate emissivity values beyond the locale of the AWS stations. Average surface temperatures can then be calculated from SSM/I brightness temperature records as well as data from other satellite sensors observing the Antarctic continent during the last 30 years.This work is thus a preliminary step to deriving a surface temperature trend across the entire Antarctic ice sheet from 1981 through to the present.