Articles | Volume 18, issue 3
https://doi.org/10.5194/amt-18-673-2025
https://doi.org/10.5194/amt-18-673-2025
Research article
 | 
06 Feb 2025
Research article |  | 06 Feb 2025

Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation

Otto Lamminpää, Jouni Susiluoto, Jonathan Hobbs, James McDuffie, Amy Braverman, and Houman Owhadi

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Cited articles

Batlle, P., Darcy, M., Hosseini, B., and Owhadi, H.: Kernel Methods are Competitive for Operator Learning, arXiv [preprint], https://doi.org/10.48550/arXiv.2304.13202, 8 October 2023. a, b
Boesch, H., Brown, L., Castano, R., Christi, M., Connor, B., Crisp, D., Eldering, A., Fisher, B., Frankenberg, C., Gunson, M., Granat, R., McDuffie, J., Miller, C., Natraj, V., O'Brien, D., O'Dell, C., Osterman, G., Oyafuso, F., Payne, V., Polonski, I., Smyth, M., Spurr, R., Thompson, D., and Toon, G.: Orbiting Carbon Observatory-2 (OCO-2) Level 2 Full Physics Retrieval Algorithm Theoretical Basis, Version 2.0, Rev 2, NASA Earth Data, https://doi.org/10.5067/8E4VLCK16O6Q, 2015. a, b, c, d
Braverman, A., Hobbs, J., Teixeira, J., and Gunson, M.: Post hoc Uncertainty Quantification for Remote Sensing Observing Systems, SIAM/ASA Journal on Uncertainty Quantification, 9, 1064–1093, https://doi.org/10.1137/19M1304283, 2021. a, b, c, d, e
Bréon, F.-M., David, L., Chatelanaz, P., and Chevallier, F.: On the potential of a neural-network-based approach for estimating XCO2 from OCO-2 measurements, Atmos. Meas. Tech., 15, 5219–5234, https://doi.org/10.5194/amt-15-5219-2022, 2022. a
Brynjarsdóttir, J., Hobbs, J., Braverman, A., and Mandrake, L.: Optimal Estimation Versus MCMC for CO2 Retrievals, J. Agr. Biol. Envir. St., 23, 297–316, https://doi.org/10.1007/s13253-018-0319-8, 2018. a, b
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Short summary
We develop and demonstrate a fast forward function emulator for remote sensing of greenhouse gases. These forward functions are computationally expensive to evaluate, and as such the key challenge for many satellite missions in their data processing is the time used in these evaluations. Our method is fast and accurate enough, less than 1 % relative error, so that it could be safely used in operational processing.
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