Articles | Volume 19, issue 7
https://doi.org/10.5194/amt-19-2407-2026
https://doi.org/10.5194/amt-19-2407-2026
Research article
 | 
14 Apr 2026
Research article |  | 14 Apr 2026

TROPOMI/WFMD v2.0: Improved retrievals of XCH4 and XCO with XGBoost-based quality filtering

Oliver Schneising, Heinrich Bovensmann, Michael Buchwitz, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Jonas Hachmeister, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, Christof Petri, Maximilian Reuter, John Robinson, Coleen Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Wei Wang, Thorsten Warneke, Damien Weidmann, Debra Wunch, Minqiang Zhou, and Hartmut Bösch

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Cited articles

Abril-Pla, O., Andreani, V., Carroll, C., Dong, L., Fonnesbeck, C. J., Kochurov, M., Kumar, R., Lao, J., Luhmann, C. C., Martin, O. A., Osthege, M., Vieira, R., Wiecki, T., and Zinkov, R.: PyMC: a modern, and comprehensive probabilistic programming framework in Python, PeerJ Computer Sci,, 9, e1516, https://doi.org/10.7717/peerj-cs.1516, 2023. a
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Balasus, N., Jacob, D. J., Lorente, A., Maasakkers, J. D., Parker, R. J., Boesch, H., Chen, Z., Kelp, M. M., Nesser, H., and Varon, D. J.: A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases, Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, 2023. a
Barr, A. G., Landgraf, J., Martinez-Velarte, M., Vrekoussis, M., Sussmann, R., Morino, I., Strong, K., Zhou, M., Velazco, V. A., Ohyama, H., Warneke, T., Hase, F., and Borsdorff, T.: Five years of GOSAT-2 retrievals with RemoTeC: XCO2 and XCH4 data products with quality filtering by machine learning, Atmos. Meas. Tech., 18, 6093–6123, https://doi.org/10.5194/amt-18-6093-2025, 2025. a
Barré, J., Aben, I., Agustí-Panareda, A., Balsamo, G., Bousserez, N., Dueben, P., Engelen, R., Inness, A., Lorente, A., McNorton, J., Peuch, V.-H., Radnoti, G., and Ribas, R.: Systematic detection of local CH4 anomalies by combining satellite measurements with high-resolution forecasts, Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, 2021. a
Short summary
We present an improved version of the TROPOMI/WFMD (TROPOspheric Monitoring Instrument/Weighting Function Modified Differential) algorithm for the simultaneous retrieval of atmospheric methane and carbon monoxide from satellite observations. The updated data product combines higher data yield with better precision and accuracy, expanding its suitability for a wider range of scientific applications. These substantial advances are mainly due to refined quality filtering, enabling more reliable identification of cloudy scenes and mitigating specific aerosol-related issues.
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