{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T01:55:15Z","timestamp":1782870915583,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T00:00:00Z","timestamp":1711670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Australian Research Council","award":["DP140101552"],"award-info":[{"award-number":["DP140101552"]}]},{"name":"Australian Research Council","award":["DP160101598"],"award-info":[{"award-number":["DP160101598"]}]},{"name":"Australian Research Council","award":["LE0668470"],"award-info":[{"award-number":["LE0668470"]}]},{"name":"Australian Research Council","award":["NAG5-12247"],"award-info":[{"award-number":["NAG5-12247"]}]},{"name":"Australian Research Council","award":["NNG05-GD07G"],"award-info":[{"award-number":["NNG05-GD07G"]}]},{"name":"Australian Research Council","award":["FT180100327"],"award-info":[{"award-number":["FT180100327"]}]},{"name":"NASA","award":["DP140101552"],"award-info":[{"award-number":["DP140101552"]}]},{"name":"NASA","award":["DP160101598"],"award-info":[{"award-number":["DP160101598"]}]},{"name":"NASA","award":["LE0668470"],"award-info":[{"award-number":["LE0668470"]}]},{"name":"NASA","award":["NAG5-12247"],"award-info":[{"award-number":["NAG5-12247"]}]},{"name":"NASA","award":["NNG05-GD07G"],"award-info":[{"award-number":["NNG05-GD07G"]}]},{"name":"NASA","award":["FT180100327"],"award-info":[{"award-number":["FT180100327"]}]},{"name":"ARC Future Fellowship","award":["DP140101552"],"award-info":[{"award-number":["DP140101552"]}]},{"name":"ARC Future Fellowship","award":["DP160101598"],"award-info":[{"award-number":["DP160101598"]}]},{"name":"ARC Future Fellowship","award":["LE0668470"],"award-info":[{"award-number":["LE0668470"]}]},{"name":"ARC Future Fellowship","award":["NAG5-12247"],"award-info":[{"award-number":["NAG5-12247"]}]},{"name":"ARC Future Fellowship","award":["NNG05-GD07G"],"award-info":[{"award-number":["NNG05-GD07G"]}]},{"name":"ARC Future Fellowship","award":["FT180100327"],"award-info":[{"award-number":["FT180100327"]}]},{"name":"NASA\u2019s Earth Science Division","award":["DP140101552"],"award-info":[{"award-number":["DP140101552"]}]},{"name":"NASA\u2019s Earth Science Division","award":["DP160101598"],"award-info":[{"award-number":["DP160101598"]}]},{"name":"NASA\u2019s Earth Science Division","award":["LE0668470"],"award-info":[{"award-number":["LE0668470"]}]},{"name":"NASA\u2019s Earth Science Division","award":["NAG5-12247"],"award-info":[{"award-number":["NAG5-12247"]}]},{"name":"NASA\u2019s Earth Science Division","award":["NNG05-GD07G"],"award-info":[{"award-number":["NNG05-GD07G"]}]},{"name":"NASA\u2019s Earth Science Division","award":["FT180100327"],"award-info":[{"award-number":["FT180100327"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The TROPOMI XCH4 data product requires rigorous cloud filtering to achieve a product accuracy of &lt;1%. To this end, operational XCH4 data processing has been based on SUOMI-NPP VIIRS cloud observations. However, SUOMI-NPP is nearing the end of its operational life and has encountered malfunctions in 2022 and 2023. In this study, we introduce a novel machine learning cloud-clearing approach based on a random forest classifier (RFC). The RFC is trained on collocated TROPOMI and SUOMI-NPP VIIRS data to emulate VIIRS-like cloud clearing. After training, cloud masking requires only TROPOMI data, and so becomes operationally independent of SUOMI-NPP. We demonstrate the RFC approach by applying cloud clearing to operational TROPOMI XCH4 data for August 2022, a period in which VIIRS was not operational. For validation, we analyze the TROPOMI XCH4 data at 12 TCCON stations. Comparison of cloud clearing using the RFC and the original VIIRS method reveals excellent agreement with a similar station-to-station bias (\u22127.4 ppb versus \u22125.6 ppb), a similar standard deviation of the station-to-station bias (11.6 ppb versus 12 ppb), and the same Pearson correlation coefficient of 0.9. Remarkably, the RFC cloud clearing provides a slightly higher volume of data (2182 versus 2035 daily means) and appears to have fewer outliers. Since 21 November 2023, the RFC approach is part of the operational processing chain of the European Space Agency (ESA). For now, the default practice is to utilize SNPP-VIIRS when accessible. Only in cases where VIIRS data are unavailable do we resort to the RFC cloud mask.<\/jats:p>","DOI":"10.3390\/rs16071208","type":"journal-article","created":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T06:33:16Z","timestamp":1711693996000},"page":"1208","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH4 Product"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4421-0187","authenticated-orcid":false,"given":"Tobias","family":"Borsdorff","sequence":"first","affiliation":[{"name":"SRON Netherlands Institute for Space Research, 2333 CA Leiden, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mari C.","family":"Martinez-Velarte","sequence":"additional","affiliation":[{"name":"SRON Netherlands Institute for Space Research, 2333 CA Leiden, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6887-5653","authenticated-orcid":false,"given":"Maarten","family":"Sneep","sequence":"additional","affiliation":[{"name":"Royal Netherlands Meteorological Institute, KNMI, 3731 GA De Bilt, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"ter Linden","sequence":"additional","affiliation":[{"name":"Royal Netherlands Meteorological Institute, KNMI, 3731 GA De Bilt, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jochen","family":"Landgraf","sequence":"additional","affiliation":[{"name":"SRON Netherlands Institute for Space Research, 2333 CA Leiden, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1853","DOI":"10.5194\/acp-13-1853-2013","article-title":"Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations","volume":"13","author":"Myhre","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1038\/ngeo1955","article-title":"Three decades of global methane sources and sinks","volume":"6","author":"Kirschke","year":"2013","journal-title":"Nat. Geosci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"14721","DOI":"10.5194\/acp-19-14721-2019","article-title":"An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data","volume":"19","author":"Lunt","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"eabn9683","DOI":"10.1126\/sciadv.abn9683","article-title":"Using satellites to uncover large methane emissions from landfills","volume":"8","author":"Maasakkers","year":"2022","journal-title":"Sci. Adv."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.rse.2011.09.027","article-title":"TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications","volume":"120","author":"Veefkind","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3682","DOI":"10.1002\/2018GL077259","article-title":"Toward Global Mapping of Methane With TROPOMI: First Results and Intersatellite Comparison to GOSAT","volume":"45","author":"Haili","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"665","DOI":"10.5194\/amt-14-665-2021","article-title":"Methane retrieved from TROPOMI: Improvement of the data product and validation of the first 2 years of measurements","volume":"14","author":"Lorente","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6585","DOI":"10.5194\/amt-15-6585-2022","article-title":"Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements","volume":"15","author":"Lorente","year":"2022","journal-title":"Atmos. Meas. Tech."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.5194\/amt-16-1597-2023","article-title":"Accounting for surface reflectance spectral features in TROPOMI methane retrievals","volume":"16","author":"Lorente","year":"2023","journal-title":"Atmos. Meas. Tech."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"26376","DOI":"10.1073\/pnas.1908712116","article-title":"Satellite observations reveal extreme methane leakage from a natural gas well blowout","volume":"116","author":"Pandey","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6249","DOI":"10.5194\/amt-14-6249-2021","article-title":"Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations","volume":"14","author":"Sha","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5423","DOI":"10.5194\/amt-9-5423-2016","article-title":"The operational methane retrieval algorithm for TROPOMI","volume":"9","author":"Hu","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"973","DOI":"10.5194\/amt-9-973-2016","article-title":"Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: Validation against collocated MODIS and CALIOP data","volume":"9","author":"Taylor","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1117\/12.2324329","article-title":"NOAA-20 VIIRS on-orbit performance, data quality, and operational Cal\/Val support","volume":"10781","author":"Cao","year":"2018","journal-title":"Earth Obs. Mission. Sens. Dev. Implement. Charact."},{"key":"ref_15","first-page":"1","article-title":"Monitoring and assimilation of S5P\/TROPOMI carbon monoxide data with the global CAMS near-real time system","volume":"2022","author":"Inness","year":"2022","journal-title":"Atmos. Chem. Phys. Discuss."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"12,673","DOI":"10.1002\/2013JD020449","article-title":"Suomi-NPP VIIRS aerosol algorithms and data products","volume":"118","author":"Jackson","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_17","unstructured":"Siddans, R. (2016). S5P-NPP Cloud Processor ATBD, Atbd, RAL, Harwell Campus."},{"key":"ref_18","unstructured":"Hasekamp, O., Lorente, A., Hu, H., Butz, A., de Brugh, J., and Landgraf, J. (2016). Algorithm Theoretical Baseline Document for Sentinel-5 Precursor Methane Retrieval, Atbd, SRON."},{"key":"ref_19","unstructured":"Landgraf, J., de Brugh, J.a., Scheepmaker, R.A., Borsdorff, T., Houweling, S., and Hasekamp, O.P. (2016). Algorithm Theoretical Baseline Document for Sentinel-5 Precursor: Carbon Monoxide Total Column Retrieval, Atbd, SRON."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2826","DOI":"10.1002\/2018GL077045","article-title":"Measuring Carbon Monoxide with TROPOMI: First Results and a Comparison With ECMWF-IFS Analysis Data","volume":"45","author":"Borsdorff","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_21","first-page":"1","article-title":"Mapping carbon monoxide pollution from space down to city scales with daily global coverage","volume":"2018","author":"Borsdorff","year":"2018","journal-title":"Atmos. Meas. Tech. Discuss."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"15761","DOI":"10.5194\/acp-20-15761-2020","article-title":"Monitoring CO emissions of the metropolis Mexico City using TROPOMI CO observations","volume":"20","author":"Borsdorff","year":"2020","journal-title":"Atmos. Chem. Phys."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"523","DOI":"10.5194\/amt-7-523-2014","article-title":"Insights into Tikhonov regularization: Application to trace gas column retrieval and the efficient calculation of total column averaging kernels","volume":"7","author":"Borsdorff","year":"2014","journal-title":"Atmos. Meas. Tech."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Butz, A., Guerlet, S., Hasekamp, O., Schepers, D., Galli, A., Aben, I., Frankenberg, C., Hartmann, J.M., Tran, H., and Kuze, A. (2011). Toward accurate CO2 and CH4 observations from GOSAT. Geophys. Res. Lett., 38.","DOI":"10.1029\/2011GL047888"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"20033","DOI":"10.1038\/s41598-019-56428-5","article-title":"Quantification of nitrogen oxides emissions from build-up of pollution over Paris with TROPOMI","volume":"9","author":"Lorente","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_26","unstructured":"Kivi, R., Heikkinen, P., and Kyr\u00f6, E. (2014). TCCON Data from Sodankyl\u00e4 (FI), Release GGG2014.R0, Finnish Meteorological Institute."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"271","DOI":"10.5194\/gi-5-271-2016","article-title":"Fourier transform spectrometer measurements of column CO2 at Sodankyl\u00e4, Finland","volume":"5","author":"Kivi","year":"2016","journal-title":"Geosci. Instrum. Methods Data Syst."},{"key":"ref_28","unstructured":"Wunch, D., Mendonca, J., Colebatch, O., Allen, N.T., Blavier, J.F., Roche, S., Hedelius, J., Neufeld, G., Springett, S., and Worthy, D. (2018). TCCON Data from East Trout Lake, SK (CA), Release GGG2014.R1, Canada Foundation for Innovation."},{"key":"ref_29","unstructured":"Hase, F., Blumenstock, T., Dohe, S., Gro\u00df, J., and Kiel, M. (2014). TCCON Data from Karlsruhe (DE), Release GGG2014.R0, Helmholtz Association of German Research Centres."},{"key":"ref_30","unstructured":"Warneke, T., Messerschmidt, J., Notholt, J., Weinzierl, C., Deutscher, N.M., Petri, C., and Grupe, P. (2014). TCCON Data from Orl\u00e9ans (FR), Release GGG2014.R0, European Union."},{"key":"ref_31","unstructured":"Wennberg, P.O., Roehl, C.M., Wunch, D., Toon, G.C., Blavier, J.F., Washenfelder, R., Keppel-Aleks, G., Allen, N.T., and Ayers, J. (2017). TCCON Data from Park Falls (US), Release GGG2014.R1, National Aeronautics and Space Administration."},{"key":"ref_32","unstructured":"Wennberg, P.O., Wunch, D., Roehl, C.M., Blavier, J.F., Toon, G.C., and Allen, N.T. (2016). TCCON Data from Lamont (US), Release GGG2014.R1, National Aeronautics and Space Administration."},{"key":"ref_33","unstructured":"Wennberg, P.O., Wunch, D., Roehl, C.M., Blavier, J.F., Toon, G.C., and Allen, N.T. (2016). TCCON Data from Caltech (US), Release GGG2014.R0, National Aeronautics and Space Administration."},{"key":"ref_34","unstructured":"Iraci, L.T., Podolske, J.R., Hillyard, P.W., Roehl, C., Wennberg, P.O., Blavier, J.F., Landeros, J., Allen, N., Wunch, D., and Zavaleta, J. (2016). TCCON Data from Edwards (US), Release GGG2014.R1, National Aeronautics and Space Administration."},{"key":"ref_35","unstructured":"Kawakami, S., Ohyama, H., Arai, K., Okumura, H., Taura, C., Fukamachi, T., and Sakashita, M. (2024, March 20). Available online: https:\/\/data.caltech.edu\/records\/n2823-2yt07."},{"key":"ref_36","unstructured":"Griffith, D.W., Deutscher, N.M., Velazco, V.A., Wennberg, P.O., Yavin, Y., Keppel-Aleks, G., Washenfelder, R.A., Toon, G.C., Blavier, J.F., and Paton-Walsh, C. (2014). TCCON Data from Darwin (AU), Release GGG2014.R0, National Aeronautics and Space Administration."},{"key":"ref_37","unstructured":"Griffith, D.W., Velazco, V.A., Deutscher, N.M., Paton-Walsh, C., Jones, N.B., Wilson, S.R., Macatangay, R.C., Kettlewell, G.C., Buchholz, R.R., and Riggenbach, M.O. (2014). TCCON Data from Wollongong (AU), Release GGG2014.R0, National Aeronautics and Space Administration."},{"key":"ref_38","unstructured":"Pollard, D.F., Robinson, J., and Shiona, H. (2019). TCCON Data from Lauder (NZ), Release GGG2014.R0, National Institute of Water and Atmospheric Research."},{"key":"ref_39","unstructured":"Sherlock, V., Connor, B., Robinson, J., Shiona, H., Smale, D., and Pollard, D.F. (2014). TCCON Data from Lauder (NZ), 125HR, Release GGG2014.R0, National Institute of Water and Atmospheric Research."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"6771","DOI":"10.5194\/amt-12-6771-2019","article-title":"A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor","volume":"12","author":"Schneising","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1109\/34.709601","article-title":"The random subspace method for constructing decision forests","volume":"20","author":"Ho","year":"1998","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"40","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_43","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"5443","DOI":"10.5194\/amt-12-5443-2019","article-title":"Improving the TROPOMI CO data product: Update of the spectroscopic database and destriping of single orbits","volume":"12","author":"Borsdorff","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2251","DOI":"10.5194\/amt-15-2251-2022","article-title":"Retrieving H2O\/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI)","volume":"15","author":"Schneider","year":"2022","journal-title":"Atmos. Meas. Tech."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.rse.2011.05.030","article-title":"TROPOMI aboard Sentinel-5 Precursor: Prospective performance of CH4 retrievals for aerosol and cirrus loaded atmospheres","volume":"120","author":"Butz","year":"2012","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1208\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:20:51Z","timestamp":1760106051000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1208"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,29]]},"references-count":46,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["rs16071208"],"URL":"https:\/\/doi.org\/10.3390\/rs16071208","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,29]]}}}