Lossless compression studies for real-time rebroadcast of data from NOAA's future advanced GOES sounders

Abstract

This paper presents systematic lossless data compression studies conducted at Cooperative Institute of Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison in support of the real-time rebroadcast of NOAA's future GOES ultraspectral sounders. Ultraspectral sounders provide data with high spectral and spatial resolutions. Since an ultraspectral sounder could be either a grating spectrometer or a Michelson interferometer, we have investigated/developed various 2D and 3D lossless compression techniques for both grating and interferometer data. The lossless compression results are obtained and compared from wavelet/multiwavelt transform-based (e.g. JPEG2000, 3D SPIHT, MWT), prediction-based (e.g. JPEG-LS, CALIC), projection-based (e.g. Lossless PCA, Optimized Orthogonal Matching Pursuit-based Linear Prediction, PLT), and clustering-based (e.g. PPVQ, FPVQ, AVQLP) methods. Robust data preprocessing schemes (e.g. BAR, MST reordering) are also demonstrated to improve compression gains of existing state-of-the-art compression methods such as JPEG2000, 3D SPIHT, JPEG-LS, and CALIC for high-spectral-resolution data compression. Our studies show that high lossless compression gains are achievable for both grating and interferometer data.