the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on updated Peking University OMI NO2 algorithm
Abstract. The TROPOspheric Monitoring Instrument (TROPOMI), onboard the Sentinel-5 Precursor (S5P) satellite launched in October 2017, is dedicated to monitoring the atmospheric composition associated with air quality and climate change. This paper presents the global retrieval of TROPOMI tropospheric formaldehyde (HCHO) and nitrogen dioxide (NO2) vertical columns using an updated version of the Peking University OMI NO2 (POMINO) algorithm, which focuses on improving the calculation of air mass factors (AMFs). The algorithm features explicit corrections for the surface reflectance anisotropy and aerosol optical effects, and uses daily high-resolution (0.25°×0.25°) a priori HCHO and NO2 profiles from the Global Earth Observing System Composition Forecast (GEOS-CF) dataset. For cloud correction, a consistent approach is used for both HCHO and NO2 retrievals, where (1) the cloud fraction is re-calculated at 440 nm using the same ancillary parameters as those used in the NO2 AMF calculation, and (2) the cloud top pressure is taken from the operational FRESCO-S cloud product.
The comparison between POMINO and reprocessed (RPRO) operational products in April, July, October 2021 and January 2022 exhibits high spatial agreement, but RPRO tropospheric HCHO and NO2 columns are lower by 10 % to 20 % over polluted regions. Sensitivity tests with POMINO show that the HCHO retrieval differences are mainly caused by different aerosol correction methods (implicit versus explicit), prior information of vertical profile shapes and background corrections; while the NO2 retrieval discrepancies result from different aerosol corrections, surface reflectances and a priori vertical profile shapes as well as their non-linear interactions. With explicit aerosol corrections, the HCHO structural uncertainty due to the cloud correction using different cloud parameters is within ± 20 %, mainly caused by cloud height differences. Validation against ground-based measurements from global Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations and the Pandonia Global Network (PGN) shows that in April, July, October 2021 and January 2022, POMINO retrievals present a comparable day-to-day correlation but a reduced bias compared to the RPRO products (HCHO: R = 0.62, NMB = −30.8 % versus R = 0.68, NMB = −35.0 %; NO2: R = 0.84, NMB = −9.5 % versus R = 0.85, NMB = −19.4 %). An improved agreement of HCHO/NO2 ratio (FNR) with PGN measurements based on POMINO retrievals is also found (R = 0.83, NMB = −18.4 % versus R = 0.82, NMB = −24.1 %). Our POMINO retrieval provides a useful source of information particularly for studies combining HCHO and NO2.
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Status: open (until 17 Dec 2024)
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RC1: 'Comment on amt-2024-182', Anonymous Referee #1, 11 Dec 2024
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The paper “Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on updated Peking University OMI NO2 algorithm”, by Zhang and co-authors, presents an updated version of the POMINO algorithm for HCHO and NO2 and its structural uncertainty in the AMF calculation. The paper is well structured. The topic fits in the scope of AMT.
One concern is the application of aerosol correction on FRESCO parameters. The FRESCO CF has been recalculated and corrected using aerosol information in UV and VIS, but the original O2-A band may be less affected by aerosol than UV/VIS, possibly introducing an overcorrecting issue. Such overcorrecting can be amplified by using the un-corrected CP.
Table 1 is a bit heavy, and I recommend to remove redundant information, such as “daily” in a priori profiles. One typo in POMINO HCHO CF is 340 instead of 440.
What is the meaning of “VCD from QA4ECV” for Mohali in Table2?
Please enlarge the font size of xaxis label in Figures 10 and 11.
Citation: https://doi.org/10.5194/amt-2024-182-RC1
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