Improvement in Humidity Profile Retrieval for Hyperspectral Sounder Using Principal Component-Based Regression Algorithm

This study is an application of the hybrid regression method to improve the accuracy of retrieved humidity profile from infrared hyperspectral sounding observations. In hybrid regression method, a weighted average of two regression products that are derived using two different forms of predictand is...

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Vydané v:IEEE journal of selected topics in applied earth observations and remote sensing Ročník 8; číslo 6; s. 3193 - 3198
Hlavní autori: Bisht, Jagat Singh Heet, Thapliyal, Pradeep Kumar, Shukla, Munn Vinayak, Kumar, Raj
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: IEEE 01.06.2015
Predmet:
Accuracy
Atmospheric measurements
Atmospheric modeling
Humidity
Hybrid regression
hyperspectral
infrared atmospheric sounding interferometer (IASI)
principal component
Principal component analysis
Satellites
Temperature measurement
principal component
infrared atmospheric sounding interferometer (IASI)
hyperspectral
Hybrid regression
ISSN:1939-1404, 2151-1535
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Shrnutí:This study is an application of the hybrid regression method to improve the accuracy of retrieved humidity profile from infrared hyperspectral sounding observations. In hybrid regression method, a weighted average of two regression products that are derived using two different forms of predictand is computed. Regression coefficients for each form of predictand are computed using principal components of MetOp-IASI radiance spectra. First regression product uses logarithm of specific humidity as predictand, whereas second regression product uses only specific humidity as predictand. The weights used in hybrid regression are computed at different pressure levels based on error statistics of humidity retrieval from different predictands. The hybrid regression-based method shows improvement over the state-of-the-art regression method. Humidity profiles retrieved from different regression methods are validated with collocated ECMWF humidity profiles and radiosonde observations for dry, wet, and combined atmospheric conditions. For all cases, humidity retrieved from hybrid regression method is found to be the most accurate at all pressure levels.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2014.2366376