Co-registration of a 1989 Antarctic Digital Elevation Model with SSM/I Brightness Temperature Data and Animation of Time Series Data

• Main Authors: Wilson, D., Jezek, K.C., Grace, S., Lampkin, D.
• Format: Report
• Language: English
• Published: Byrd Polar Research Center, The Ohio State University. 1992
• Subjects: Special Sensor Microwave/Imager (SSM/I); Digital Elevation Model (DEM); Microwave brightness temperatures; Polar ice sheets; Antarctic; Antarc*; Antarctica; Ice Sheet; National Snow and Ice Data Center; Polar Research; Scott Polar Research Institute; Sea ice
• Online Access: http://hdl.handle.net/1811/51368

The Special Sensor Microwave/Imager (SSM/I) instrument provides daily measures of microwave brightness temperatures (Tb) over the polar regions. Data are available from 1987 to the present and these data have a demonstrated utility for sea ice studies. In this paper we investigate applications to polar ice sheets with a view towards correlating patterns of Tb with ice sheet elevation. Our approach consists of combining SSM/I Tb values provided on CDROM by the National Snow and Ice Data Center with a digital elevation map (DEM) of Antarctica derived originally from the Scott Polar Research Institute Antarctic Map Folio. We focused on 37 GHz data which are mapped onto a 316 x 332 polar stereographic grid at 25-km resolution. The DEM consists of a 281 x 281 array of elevation values with a 20-km resolution. The DEM was resampled to be compatible with the SSM/I data set by transforming the elevation data from the original projection plane to geodetic coordinates. The elevation data were then transformed onto the SSM/I projection plane. Elevation data were interpolated to yield ice sheet surface heights at 25-km intervals coinciding with SSM/I point Tb assignments. By co-registering the two data sets, it is possible to 'drape' the brightness temperature data over the DEM. The resulting image highlights the relationship (and variations) between ice sheet topography and brightness temperature. A time series of merged data sets is presented in animated form that facilitates studies of the annual temperature cycle.