Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products

Creators: Schneider, Matthias; Ertl, Benjamin; Tu, Qiansi; Diekmann, Christopher J.; Khosrawi, Farahnaz; Röhling, Amelie N.; Hase, Frank; Dubravica, Darko; García, Omaira E.; Sepúlveda, Eliezer; Borsdorff, Tobias; Landgraf, Jochen; Lorente, Alba; Butz, André; Chen, Huilin; Kivi, Rigel; Laemmel, Thomas; Ramonet, Michel; Crevoisier, Cyril; Pernin, Jérome; Steinbacher, Martin; Meinhardt, Frank; Strong, Kimberly; Wunch, Debra; Warneke, Thorsten; Roehl, Coleen; Wennberg, Paul O.; Morino, Isamu; Iraci, Laura T.; Shiomi, Kei; Deutscher, Nicholas M.; Griffith, David W. T.; Velazco, Voltaire A.; Pollard, David F.

Abstract

The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near-infrared and/or shortwave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument), offer higher sensitivity near the ground and are used for the retrieval of total-column-averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total-column level 2 retrieval products. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach has strong theoretical similarities to applying the spectra of the different sensors together in a single retrieval procedure but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH₄). We perform a theoretical evaluation and show that the a posteriori combination method yields a total-column-averaged CH₄ product (XCH₄) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the high-quality upper troposphere–lower stratosphere (UTLS) CH₄ partial-column information of the corresponding IASI product. As a consequence, the combined product offers additional sensitivity for the tropospheric CH₄ partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effect is verified by comparisons to CH₄ reference data obtained from collocated XCH₄ measurements at 14 globally distributed TCCON (Total Carbon Column Observing Network) stations, CH₄ profile measurements made by 36 individual AirCore soundings, and tropospheric CH₄ data derived from continuous ground-based in situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect the actual variations of atmospheric XCH₄, CH₄ in the UTLS, and CH₄ in the troposphere. A similar good reliability for the latter is not achievable by the individual TROPOMI and IASI products.

Additional Information

© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 9 February 2021 – Discussion started: 23 February 2021. Revised: 13 April 2022 – Accepted: 30 May 2022 – Published: 29 July 2022. This research has largely benefitted from funds of the Deutsche Forschungsgemeinschaft (provided for the two projects MOTIV and TEDDY with IDs/Geschäftszeichen 290612604/GZ:SCHN1126/2-1 and 416767181/GZ:SCHN1126/5-1, respectively) and from support by the European Space Agency in the context the "Sentinel-5p+Innovation (S5p+I) – Water Vapour Isotopologues (H2O-ISO)" activities. Furthermore, we acknowledge funds from the Ministerio de Economía y Competividad from Spain for the project INMENSE (CGL2016-80688-P). An important part of this work was performed on the supercomputers ForHLR and HoreKa funded by the Ministry of Science, Research and the Arts Baden-Württemberg and by the German Federal Ministry of Education and Research. We also acknowledge the contribution of Teide High-Performance Computing facilities. Teide HPC facilities are provided by the Instituto Tecnológico y de Energías Renovables (ITER), S.A (https://teidehpc.iter.es/en/home/, last access: 5 July 2022). The TROPOMI data processing was carried out on the Dutch National e-Infrastructure with the support of the SURF cooperative. The presented material contains modified Copernicus data (2017, 2019). The Eureka TCCON measurements were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change, primarily supported by NSERC, ECCC, and CSA. The East Trout Lake TCCON station is supported by CFI, ORF, and NSERC. The Karlsruhe TCCON station has been supported by the German Bundesministerium für Wirtschaft und Energie (BMWi) via DLR under grants 50EE1711A to E and by the Helmholtz Society via the research program ATMO. The Park Falls and Lamont TCCON sites are supported by and would like to acknowledge NASA's Carbon Cycle Science Program (grant no. NNX17AE15G) and OCO-2 and OCO-3 projects (primary grant no. NNN12AA01C), respectively. The Burgos and Rikubetsu TCCON sites are supported in part by the GOSAT series project. Burgos is supported in part by the Energy Development Corp., the Philippines. Funding for the Edwards TCCON station is provided by NASA's Earth Science Division. Nicholas M. Deutscher is funded by ARC Future Fellowship FT180100327. Darwin and Wollongong TCCON stations are supported by ARC grants DP160100598, LE0668470, DP140101552, DP110103118, and DP0879468 and Darwin through NASA grants NAG5-12247 and NNG05-GD07G. The Lauder TCCON programme is core-funded by NIWA through New Zealand's Ministry of Business, Innovation and Employment. The Trainou AirCore measurements have been supported by CEA, CNES, UVSQ, IPSL, and the EU H2020 RINGO project (GA no. 730944) and are part of the French consortium for Aircore measurements (LMD, LSCE, GSMA, CNES). The Sodankylä TCCON and AirCore measurements have been supported via the ESA FRM4GHG project (under grant agreement no. ESA-IPLPOE-LG-cl-LE-2015-1129) and the EU H2020 RINGO project. The CH4 observations at Jungfraujoch were established as part of the Swiss National Air Pollution Monitoring Network and are supported through ICOS-CH, which is funded by the Swiss National Science Foundation and in-house contributions. We would like to thank our colleague Thomas von Clarmann for his strong support in revising the equations in the Appendix of this paper. We thank Michela Giusti in the Data Support team at ECMWF for retrieving and providing comments about the CAMS data. We acknowledge the support by the Deutsche Forschungsgemeinschaft and the Open Access Publishing Fund of the Karlsruhe Institute of Technology. This research has been supported by the Deutsche Forschungsgemeinschaft (project MOTIV (grant no. 290612604), and project TEDDY (grant no. 416767181)), the Ministerio de Economía y Competitividad (grant no. CGL2016-80688-P), the European Space Agency (grant nos. 4000127561/19/I-NS and ESA-IPLPOE-LG-cl-LE-2015-1129), the Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg, and the Bundesministerium für Bildung und Forschung for funding in the context of the ForHLR and HoreKa supercomputing infrastructure. The article processing charges for this open-access publication were covered by the Karlsruhe Institute of Technology (KIT). Author contributions. MSc developed the idea for the optimal a posteriori combination of the level 2 remote-sensing products, and he prepared the figures and the manuscript. BE developed and performed the continuous MUSICA IASI data processing, where he was supported by MSc, CJD, FK, ANR, OEG, and ES. FH developed the PROFFIT-nadir retrieval code used for the MUSICA IASI processing. QT supported the use of the CAMS high-resolution data. TB, JL, AL, and AB are responsible for the TROPOMI processing and for making TROPOMI data available. HC and RK are responsible for the AirCore profile measurements over Sodankylä. TL, MR, CC, and JP are responsible for the AirCore profile measurements over Trainou. MSt and FM are responsible for the GAW data of Jungfraujoch and Schauinsland, respectively. RK, DD, FH, KSt, DW, TW, CR, POW, IM, LTI, KSh, NMD, DWTG, VAV, and DFP are responsible for the TCCON data. All authors supported the generation of the final version of this paper. Data availability. The MUSICA IASI data are described in (Schneider et al., 2022) and can be accessed at https://doi.org/10.35097/408 (Schneider et al., 2021a) and https://doi.org/10.35097/412 (Schneider et al., 2021b). The TROPOMI XCH4 data used in this study are described in Lorente et al. (2021a) and can be accessed at https://doi.org/10.5281/zenodo.4447228 (Lorente et al., 2021b). The TCCON data are available via the TCCON data archive, hosted by CaltechDATA (Total Carbon Column Observing Network Team, 2014, https://doi.org/10.14291/TCCON.GGG2014). For Trainou AirCore data, please contact Michel Ramonet (michel.ramonet@lsce.ipsl.fr), and for Sodankylä AirCore data, please contact Huilin Chen (huilin.chen@rug.nl). The Jungfraujoch GAW surface in situ CH4 data are available via the World Data Centre for Greenhouse Gases (WDCGG) and can be directly accessed at https://doi.org/10.50849/WDCGG_0023-6036-1002-01-01-9999 (Steinbacher, 2022). The Schainsland GAW surface in situ CH4 data up to 31 December 2018 are available via the WDCGG at https://gaw.kishou.go.jp/search/station#SSL (Meinhardt, 2019). For the Schauinsland CH4 data for 2019 and 2020, please contact Frank Meinhardt (frank.meinhardt@uba.de). The fused "MUSICA IASI/RemoTeC TROPOMI" example data presented in Fig. 15 are accessible at https://doi.org/10.35097/689 (Schneider and Ertl, 2022a). As already stated in Sect. 2.1, in this work we use the TROPOMI XCH4 data generated by the operational processing algorithm version 2.2.0 as input for the data fusion. For the example months of Fig. 15, we make additional data fusion calculations using the TROPOMI CH4 operational processing algorithm version 2.3.1, which among others offers additional coverage over ocean using glint mode observations. These fused "MUSICA IASI/RemoTeC TROPOMI" data are accessible at https://doi.org/10.35097/690 (Schneider and Ertl, 2022b). The contact author has declared that neither they nor their co-authors have any competing interests.

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