Updated validation of ACE and OSIRIS ozone and NO2 measurements in the Arctic using ground-based instruments at Eureka, Canada

Bognar, Kristof; Zhao, Xiaoyi; Strong, Kimberly; Boone, C. D.; Bourassa, A. E.; Degenstein, D. A.; Drummond, J. R.; Duff, Alan D.; Goutail, Florence; Griffin, Debora; Jeffery, Paul S.; Lutsch, Erik; Manney, G. L.; McElroy, C. T.; McLinden, Chris A.; Millán, Luis; Pazmiño, Andréa; Sioris, Christopher E.; Walker, Kaley A.; Zou, J.

doi:10.1016/j.jqsrt.2019.07.014

Cited by 19 publications

(36 citation statements)

References 66 publications

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“…Satellite tropospheric NO 2 column data are compared classically to correlative measurements acquired by Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments (Hönninger and Platt, 2002;Hönninger et al, 2004;. From sunrise to sunset, MAX-DOAS instruments measure the UV-visible radiance scattered in several directions and elevation angles, from which the tropospheric vertical column density (VCD) and/or the lowest part of the tropospheric NO 2 profile (usually up to 3 km altitude, and up to 10 km at best) can be retrieved through different techniques (see, for example, Clémer et al, 2010;Hendrick et al, 2014;Friedrich et al, 2019;Bösch et al, 2018;Irie et al, 2008Irie et al, , 2011Vlemmix et al, 2010;Wagner et al, 2011;Beirle et al, 2019), with between 1 and 3 degrees of freedom. Their horizontal spatial representativeness varies with the aerosol load and the spectral region of the retrieval, from a few kilometres to tens of kilometres (Irie et al, 2011;Wagner et al, 2011;Wang et al, 2014).…”

Section: Max-doas Datamentioning

confidence: 99%

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

et al. 2021

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Abstract. This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

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Section: Max-doas Datamentioning

confidence: 99%

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

et al. 2021

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“…The ZSL-DOAS ozone columns are total columns, while ZSL-DOAS NO 2 columns are 12-60 km partial columns. For a more detailed description of the ZSL-DOAS instruments and retrieval procedures, as well as comparisons of the GBS and SAOZ data, see Bognar et al (2019).…”

Section: Zsl-doas Measurementsmentioning

confidence: 99%

“…Pandora direct-sun measurements are limited to a few days in spring 2020, due in part to the lack of on-site support. (Adams, Strong, Batchelor, et al, 2012;Bognar et al, 2019).…”

Section: The Spring 2020 Measurements In Contextmentioning

confidence: 99%

Unprecedented Spring 2020 Ozone Depletion in the Context of 20 Years of Measurements at Eureka, Canada

et al. 2021

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In the winter and spring of 2019/2020, the unusually cold, strong, and stable polar vortex created favorable conditions for ozone depletion in the Arctic. Chemical ozone loss started earlier than in any previous year in the satellite era and continued until late March, resulting in the unprecedented reduction of the ozone column. The vortex was located above the Polar Environment Atmospheric Research Laboratory in Eureka, Canada (80°N, 86°W) from late February to the end of April, presenting an excellent opportunity to examine ozone loss from a single ground station. Measurements from a suite of instruments show that total column ozone was at an all-time low in the 20-year data set, 22-102 DU below previous records set in 2011. Ozone minima (<200 DU), enhanced OClO and BrO slant columns, and unusually low-HCl, ClONO 2 , and HNO 3 columns were observed in March. Polar stratospheric clouds were present as late as 20 March, and ozonesondes show unprecedented depletion in the March and April profiles (to <0.2 ppmv). While both chemical and dynamical factors lead to reduced ozone when the vortex is cold, the contribution of chemical depletion (based on the variable correlation of ozone and temperature) was exceptional in spring 2020 when compared to typical Arctic winters. Mean chemical ozone loss over Eureka was estimated to be 111-126 DU (27%-31%) using April measurements and passive ozone from the SLIMCAT chemical transport model. While absolute ozone loss was generally smaller in 2020 than in 2011, percentage ozone loss was greater in 2020.Plain Language Summary While an ozone hole forms over Antarctica every year, the Arctic typically does not experience such dramatic ozone loss. The chlorine and bromine (halogen) reactions that destroy ozone require very low temperatures that are rarely observed in the Arctic stratosphere. The winter and spring of 2019/2020, however, was unusually cold in the Arctic, and consequently, a large amount of ozone was destroyed by halogen chemistry. To understand the behavior of ozone in spring 2020, we use measurements from the Polar Environment Atmospheric Research Laboratory in Eureka, Canada. Eureka (at 80°N) is one of the northernmost research stations in the world, and thus an ideal location to observe ozone loss. Spring 2020 ozone minima were lower than any in the 20-year data set, and ozone destruction was ongoing until the end of March, which is rare in the Arctic. While ozone concentrations are largely determined by circulation patterns in the Arctic stratosphere, chemistry in spring 2020 was a much larger factor than usual. Halogen chemistry destroyed 27%-31% of the total ozone, compared to about 10% in a typical winter. The only year on record with comparable ozone loss is 2011, and a larger percentage of the ozone column was lost in 2020. BOGNAR ET AL.

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“…Analysis using "Observing System Simulation Experiments" at a fine spatial resolution (Verhoelst et al, 2015) or other experimental set-ups (e.g. sensors measuring in multiple azimuth directions; Brinksma et al, 2008;Ortega et al, 2015) can improve on this.…”

Section: Horizontal Sampling Diff Error E Rmentioning

confidence: 99%

“…However, the quality of these data sets needs to be carefully assessed using ground-based measurements at different sites (see e.g. Petritoli et al, 2004;Pinardi et al, 2014;Heue et al, 2005;Brinksma et al, 2008;Celarier et al, 2008, for validations on GOME, Global Ozone Monitoring Experiment; GOME-2, Global Ozone Monitoring Experiment-2; SCIAMACHY, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography; and OMI, Ozone Monitoring Instrument data). A limitation often encountered is that uncertainties in satellite and/or groundbased data are not adequately characterized, and the groundbased data sets are generally not harmonized across networks.…”

Section: Introductionmentioning

confidence: 99%

Validation of Aura-OMI QA4ECV NO2 climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

et al. 2020

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Abstract. The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 Pmolec.cm-2 (5 %–10 %) and a dispersion of 0.2 to 1 Pmolec.cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec.cm-2) up to −10 Pmolec.cm-2 (−40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec.cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.

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Updated validation of ACE and OSIRIS ozone and NO2 measurements in the Arctic using ground-based instruments at Eureka, Canada

Cited by 19 publications

References 66 publications

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO<sub>2</sub> measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO<sub>2</sub> measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Unprecedented Spring 2020 Ozone Depletion in the Context of 20 Years of Measurements at Eureka, Canada

Validation of Aura-OMI QA4ECV NO<sub>2</sub> climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

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Updated validation of ACE and OSIRIS ozone and NO2 measurements in the Arctic using ground-based instruments at Eureka, Canada

Cited by 19 publications

References 66 publications

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO&lt;sub&gt;2&lt;/sub&gt; measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO&lt;sub&gt;2&lt;/sub&gt; measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Unprecedented Spring 2020 Ozone Depletion in the Context of 20 Years of Measurements at Eureka, Canada

Validation of Aura-OMI QA4ECV NO&lt;sub&gt;2&lt;/sub&gt; climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

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Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO<sub>2</sub> measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO<sub>2</sub> measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Validation of Aura-OMI QA4ECV NO<sub>2</sub> climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties