Priority-based error correction using turbo codes for compressed AIRS data

Errors due to wireless transmission can have an arbitrarily large impact on a compressed file. A single bit error appearing in the compressed file can propagate during a decompression procedure and destroy the entire granule. Such a loss is unacceptable since this data is critical for a range of applications, including weather prediction and emergency response planning. The impact of a bit error in the compressed granule is very sensitive to the error's location in the file. There is a natural hierarchy of compressed data in terms of impact on the final retrieval products. For the considered compression scheme, errors in some parts of the data yield no noticeable degradation in the final products. We formulate a priority scheme for the compressed data and present an error correction approach based on minimizing impact on the retrieval products. Forward error correction codes (e.g., turbo, LDPC) allow the tradeoff between error correction strength and file inflation (bandwidth expansion). We propose segmenting the compressed data based on its priority and applying different-strength FEC codes to different segments. In this paper we demonstrate that this approach can achieve negligible product degradation while maintaining an overall 3-to-1 compression ratio on the final file. We apply this to AIRS sounder data to demonstrate viability for the sounder on the next-generation GOES-R platform.