0000000000248536

AUTHOR

Joaquin Garcia-sobrino

showing 2 related works from this author

Improved Statistically Based Retrievals via Spatial-Spectral Data Compression for IASI Data

2019

In this paper, we analyze the effect of spatial and spectral compression on the performance of statistically based retrieval. Although the quality of the information is not com- pletely preserved during the coding process, experiments reveal that a certain amount of compression may yield a positive impact on the accuracy of retrievals. We unveil two strategies, both with interesting benefits: either to apply a very high compression, which still maintains the same retrieval performance as that obtained for uncompressed data; or to apply a moderate to high compression, which improves the performance. As a second contribution of this paper, we focus on the origins of these benefits. On the one…

Computer scienceInfrared Atmospheric Sounding Interferometer (IASI)Spectral Transforms0211 other engineering and technologies02 engineering and technologyData_CODINGANDINFORMATIONTHEORYLossy compressionInfrared atmospheric sounding interferometer (IASI)Kernel MethodsElectrical and Electronic EngineeringTransform coding021101 geological & geomatics engineeringbusiness.industryDimensionality reductionLossy CompressionJPEG 2000Kernel methodsPattern recognitioncomputer.file_formatJoint Photographic Experts Group (JPEG) 2000RegressionUncompressed videoSpectral transformsKernel methodStatistically based retrievalJPEG 2000General Earth and Planetary SciencesLossy compressionArtificial intelligencebusinessStatistically Based RetrievalcomputerSmoothingIEEE Transactions on Geoscience and Remote Sensing
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Statistical atmospheric parameter retrieval largely benefits from spatial-spectral image compression

2021

The infrared atmospheric sounding interferometer (IASI) is flying on board of the Metop satellite series, which is part of the EUMETSAT Polar System. Products obtained from IASI data represent a significant improvement in the accuracy and quality of the measurements used for meteorological models. Notably, the IASI collects rich spectral information to derive temperature and moisture profiles, among other relevant trace gases, essential for atmospheric forecasts and for the understanding of weather. Here, we investigate the impact of near-lossless and lossy compression on IASI L1C data when statistical retrieval algorithms are later applied. We search for those compression ratios that yield…

MeteorologySatellites0211 other engineering and technologies02 engineering and technologyAtmospheric modelLossy compressionInfrared atmospheric sounding interferometerAtmospheric measurements0202 electrical engineering electronic engineering information engineeringTransform codingElectrical and Electronic EngineeringTransform coding021101 geological & geomatics engineeringRemote sensingTemperature measurementHyperspectral imagingImage coding020206 networking & telecommunicationsTransformsDepth soundingAtmospheric modelingDew point13. Climate actionCompression ratioGeneral Earth and Planetary SciencesEnvironmental science
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