Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations
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Published:2022-04-13
Issue:7
Volume:15
Page:2199-2229
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ISSN:1867-8548
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Container-title:Atmospheric Measurement Techniques
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language:en
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Short-container-title:Atmos. Meas. Tech.
Author:
Alberti CarlosORCID, Tu Qiansi, Hase Frank, Makarova Maria V.ORCID, Gribanov Konstantin, Foka Stefani C.ORCID, Zakharov Vyacheslav, Blumenstock ThomasORCID, Buchwitz MichaelORCID, Diekmann ChristopherORCID, Ertl BenjaminORCID, Frey Matthias M.ORCID, Imhasin Hamud Kh., Ionov Dmitry V.ORCID, Khosrawi FarahnazORCID, Osipov Sergey I., Reuter MaximilianORCID, Schneider MatthiasORCID, Warneke Thorsten
Abstract
Abstract. This work employs ground- and space-based observations, together
with model data, to study columnar abundances of atmospheric trace gases
(XH2O, XCO2, XCH4 and XCO) in two high-latitude Russian cities, St. Petersburg and Yekaterinburg. Two portable COllaborative Column
Carbon Observing Network (COCCON) spectrometers were used for continuous
measurements at these locations during 2019 and 2020. Additionally, a subset of data of special interest (a strong gradient in XCH4 and XCO was detected) collected in the framework of a mobile city campaign performed in 2019 using both instruments is investigated. All studied satellite products (TROPOMI, OCO-2, GOSAT, MUSICA IASI) show generally good agreement with COCCON observations. Satellite and ground-based observations at high latitudes are much sparser than at low or mid latitudes, which makes direct
coincident comparisons between remote-sensing observations more difficult.
Therefore, a method of scaling continuous Copernicus Atmosphere
Monitoring Service (CAMS) model data to the
ground-based observations is developed and used for creating virtual COCCON
observations. These adjusted CAMS data are then used for satellite
validation, showing good agreement in both Peterhof and Yekaterinburg. The gradients between the two study sites (ΔXgas) are
similar between CAMS and CAMS-COCCON datasets, indicating that the model
gradients are in agreement with the gradients observed by COCCON. This is
further supported by a few simultaneous COCCON and satellite ΔXgas
measurements, which also agree with the model gradient. With respect to the
city campaign observations recorded in St Petersburg, the downwind COCCON
station measured obvious enhancements for both XCH4 (10.6 ppb) and XCO (9.5 ppb), which is nicely reflected by TROPOMI observations, which detect city-scale gradients of the order 9.4 ppb for XCH4 and 12.5 ppb for XCO.
Funder
Horizon 2020 Framework Programme
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference86 articles.
1. Alberti, C., Hase, F., Frey, M., Dubravica, D., Blumenstock, T., Dehn, A., Surawicz, G., Harig, R., Orphal, J., and the EM27/SUN-partners team: Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON), Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2021-395, in review, 2021. 2. Bergamaschi, P., Krol, M., Meirink, J. F., Dentener, F., Segers, A., van
Aardenne, J., Monni, S., Vermeulen, A. T., Schmidt, M., Ramonet, M., Yver,
C., Meinhardt, F., Nisbet, E. G., Fisher, R. E., O'Doherty, S., and
Dlugokencky, E. J.: Inverse modeling of European CH4 emissions 2001–2006,
J. Geophys. Res., 115, D22309, https://doi.org/10.1029/2010JD014180, 2010. 3. 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. 4. Borger, C., Schneider, M., Ertl, B., Hase, F., García, O. E., Sommer, M., Höpfner, M., Tjemkes, S. A., and Calbet, X.: Evaluation of MUSICA IASI tropospheric water vapour profiles using theoretical error assessments and comparisons to GRUAN Vaisala RS92 measurements, Atmos. Meas. Tech., 11, 4981–5006, https://doi.org/10.5194/amt-11-4981-2018, 2018. 5. Borsdorff, T., Aan de Brugh, J., Hu, H., Aben, I., Hasekamp, O., and
Landgraf, J.: Measuring Carbon Monoxide With TROPOMI: First Results and a
Comparison With ECMWF-IFS Analysis Data, Geophys. Res. Lett., 45,
2826–2832, https://doi.org/10.1002/2018GL077045, 2018a.
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