Articles | Volume 15, issue 11
https://doi.org/10.5194/amt-15-3401-2022
https://doi.org/10.5194/amt-15-3401-2022
Research article
 | 
09 Jun 2022
Research article |  | 09 Jun 2022

Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm

Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke

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Cited articles

Barret, B., Gouzenes, Y., Le Flochmoen, E., and Ferrant, S.: Retrieval of Metop-A/IASI N2O Profiles and Validation with NDACC FTIR Data, Atmosphere, 12, 219, https://doi.org/10.3390/atmos12020219, 2021. a, b, c, d
Bergamaschi, P., Houweling, S., Segers, A., Krol, M., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Wofsy, S. C., Kort, E. A., Sweeney, C., Schuck, T., Brenninkmeijer, C., Chen, H., Beck, V., and Gerbig, C.: Atmospheric CH4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res.-Atmos., 118, 7350–7369, https://doi.org/10.1002/jgrd.50480, 2013. a
Blumenstock, T., Hase, F., Schneider, M., García, O. E., and Sepúlveda, E.: TCCON data from Izana (ES), Release GGG2014.R1, Caltech Library [data set], https://doi.org/10.14291/TCCON.GGG2014.IZANA01.R1, 2017. a
Boesch, H., Deutscher, N. M., Warneke, T., Byckling, K., Cogan, A. J., Griffith, D. W. T., Notholt, J., Parker, R. J., and Wang, Z.: HDO/H2O ratio retrievals from GOSAT, Atmos. Meas. Tech., 6, 599–612, https://doi.org/10.5194/amt-6-599-2013, 2013. a, b
Borger, C., Beirle, S., and Wagner, T.: Analysis of global trends of total column water vapour from multiple years of OMI observations, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-149, in review, 2022. a
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products. In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.