Ultraspectral sounders provide an enormous amount of measurements to advance our knowledge of weather and climate applications. The use of robust data compression techniques will be beneficial for ultraspectral data transfer and archiving. This paper reviews the progress in lossless compression of ultraspectral sounder data. Various transform-based, prediction-based, and clustering-based compression methods are covered. Also studied is a preprocessing scheme for data reordering to improve compression gains. All the coding experiments are performed on the ultraspectral compression benchmark dataset collected from the NASA Atmospheric Infrared Sounder (AIRS) observations.
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