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Application of a PCA-based Fast Radiative Transfer Model to XCO_2 Retrievals in the Shortwave Infrared

Somkuti, P. and Boesch, H. and Natraj, V. and Kopparla, P. (2017) Application of a PCA-based Fast Radiative Transfer Model to XCO_2 Retrievals in the Shortwave Infrared. Journal of Geophysical Research. Atmospheres, 122 (19). pp. 10477-10496. ISSN 2169-897X. doi:10.1002/2017JD027013.

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In this work, we extend the principal component analysis (PCA)-based approach to accelerate radiative transfer (RT) calculations by accounting for the spectral variation of aerosol properties. Using linear error analysis, the errors induced by this fast RT method are quantified for a large number of simulated Greenhouse Gases Observing Satellite (GOSAT) measurements (N≈ 30,000). The computational speedup of the approach is typically 2 orders of magnitude compared to a line-by-line discrete ordinates calculation with 16 streams, while the radiance residuals do not exceed 0.01% for the most part compared to the same baseline calculations. We find that the errors due to the PCA-based approach tend to be less than ±0.06 ppm for both land and ocean scenes when two or more empirical orthogonal functions are used. One advantage of this method is that it maintains the high accuracy over a large range of aerosol optical depths. This technique shows great potential to be used in operational retrievals for GOSAT and other remote sensing missions.

Item Type:Article
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URLURL TypeDescription
Somkuti, P.0000-0002-5858-8471
Boesch, H.0000-0003-3944-9879
Natraj, V.0000-0003-3154-9429
Kopparla, P.0000-0002-8951-3907
Additional Information:©2017 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Received 21 APR 2017; Accepted 1 SEP 2017; Accepted article online 11 SEP 2017; Published online 12 OCT 2017. P. Somkuti is funded by the ESA Greenhouse Gas Climate Change Initiative (GHG-CCI) as part of a PhD studentship. H. Boesch receives funding by the UK National Centre for Earth Observation (NCEO) as well as GHG-CCI. V. Natraj was supported by the Orbiting Carbon Observatory (OCO-2) Project at the Jet Propulsion Laboratory, California Institute of Technology. P. Kopparla was supported in part by the NASA NNX13AK34G grant to the California Institute of Technology and the OCO-2 Project at the Jet Propulsion Laboratory. We thank the Japanese Aerospace Exploration Agency, National Institute for Environmental Studies, and the Ministry of Environment for the GOSAT data and their continuous support as part of the Joint Research Agreement. GOSAT L1B data are available from the GOSAT data archive service (GDAS, ECMWF ERA-Interim data are available through the ECMWF website ( THE ESA-CCI land cover classification data can be obtained from The radiance residuals as well as the associated XCO_2 errors are available as HDF5 files from The authors would like to thank R. Parker for helpful comments and editing, as well as L. Vogel for assistance regarding the aerosol scheme. We thank the two anonymous reviewers as well as the editor for their feedback and helping to improve the quality of this publication. This research used the ALICE/SPECTRE High Performance Computing Facility at the University of Leicester.
Funding AgencyGrant Number
European Space Agency (ESA)UNSPECIFIED
National Centre for Earth ObservationUNSPECIFIED
Subject Keywords:Radiative Transfer; Remote Sensing; Carbon Dioxide
Issue or Number:19
Record Number:CaltechAUTHORS:20170911-155232382
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Official Citation:Somkuti, P., Boesch, H., Vijay, N., & Kopparla, P. (2017). Application of a PCA-based fast radiative transfer model to XCO2 retrievals in the shortwave infrared. Journal of Geophysical Research: Atmospheres, 122, 10,477–10,496.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:81329
Deposited By: Tony Diaz
Deposited On:11 Sep 2017 23:35
Last Modified:15 Nov 2021 19:42

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