A comprehensive characterization of frequency distribution of individual fields (reflectivity, Doppler velocity, spectrum width) and combined fields was conducted. Based on this information, several standard compression algorithms were applied (zeroth-order Huffman and arithmetic, UNIX compress) to analyze the resulting compression ratio (CR). It turns out that algorithms based on the Burrows-Wheeler Transformation (BWT) provide a very good compromise between space/time complexity and CR. The Burrows-Wheeler algorithm is a hybrid scheme combining several strategies including move-to-front heuristic, run-length coding and Huffman/Arithmetic on top of BWT. We present CR of NEXRAD radar data for various weather regimes including clear air, squall line, hurricane, and stratiform rain using the Burrows-Wheeler algorithm bzip2. We found that CR for the precipitation events analyzed range between 6:1 to as high as 11:1. CR for the clear air events analyzed range between 10:1 and 25:1. Finally we show how simple radar data preprocessing can improve the above stated CR by 10-25%.