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A fast and sensitive new satellite SO 2 retrieval algorithm based on principal component analysis: Application to the ozone monitoring instrument
Author(s) -
Li Can,
Joiner Joanna,
Krotkov Nickolay A.,
Bhartia Pawan K.
Publication year - 2013
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2013gl058134
Subject(s) - radiance , ozone monitoring instrument , remote sensing , principal component analysis , hyperspectral imaging , environmental science , satellite , radiative transfer , rayleigh scattering , algorithm , computer science , ozone depletion , meteorology , ozone , optics , physics , geology , astronomy , artificial intelligence
We describe a new algorithm to retrieve SO 2 from satellite‐measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO 2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO 2 Jacobians calculated with a radiative transfer model to directly estimate SO 2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5–340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument‐specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing long‐term, consistent SO 2 records for air quality and climate research.