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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2020-123
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-123
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Jul 2020

01 Jul 2020

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This preprint is currently under review for the journal AMT.

TROPOMI tropospheric ozone column data: Geophysical assessment and comparison to ozonesondes, GOME-2B and OMI

Daan Hubert1, Klaus-Peter Heue2,3, Jean-Christopher Lambert1, Tijl Verhoelst1, Marc Allaart4, Steven Compernolle1, Patrick D. Cullis5, Angelika Dehn6, Christian Félix7, Bryan J. Johnson5, Arno Keppens1, Debra E. Kollonige8,9, Christophe Lerot1, Diego Loyola2, Matakite Maata10, Sukarni Mitro11, Maznorizan Mohamad12, Ankie Piters4, Fabian Romahn2, Henry B. Selkirk9,13, Francisco R. da Silva14, Ryan M. Stauffer9,15, Anne M. Thompson9, J. Pepijn Veefkind4, Holger Vömel16, Jacquelyn C. Witte16, and Claus Zehner6 Daan Hubert et al.
  • 1Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Uccle (Brussels), Belgium
  • 2German Aerospace Centre (DLR), Münchener Straße 20, 82234 Weßling, Germany
  • 3Technische Universität München, Arcisstrasse 21, 80333 München, Germany
  • 4Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3730 AE De Bilt, The Netherlands
  • 5NOAA Global Monitoring Laboratory (NOAA/ESRL/GML), 1325 Broadway, Boulder 80305-3337, CO, USA
  • 6European Space Agency/Centre for Earth Observation (ESA/ESRIN), Largo Galileo Galilei 1, 00044 Frascati (Roma), Italy
  • 7Federal Office of Meteorology and Climatology, MeteoSwiss, Payerne, Switzerland
  • 8Science Systems and Applications, Inc., Lanham, MD, USA
  • 9Atmospheric Chemistry and Dynamics Lab, NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 10School of Biological and Chemical Sciences, University of the South Pacific, Fiji
  • 11Meteorological Service of Suriname, Paramaribo, Suriname
  • 12Atmospheric Science and Cloud Seeding Division, Malaysian Meteorological Department, Petaling Jaya, Selangor, Malaysia
  • 13Universities Space Research Association, Columbia, MD, USA
  • 14Laboratory of Environmental and Tropical Variables, Brazilian Institute of Space Research, Natal, Brazil
  • 15Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
  • 16National Center for Atmospheric Research, Boulder, CO, USA

Abstract. Ozone in the troposphere affects humans and ecosystems as a pollutant and as a greenhouse gas. Observing, understanding and modelling this dual role, as well as monitoring effects of international regulations on air quality and climate change, however, challenge measurement systems to operate at opposite ends of the spatio-temporal scale ladder. On board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite launched in October 2017, TROPOspheric Monitoring Instrument (TROPOMI) aspires to take the next leap forward by measuring ozone and its precursors at unprecedented horizontal resolution until at least the mid 2020s. In this work, we assess the quality of TROPOMI's first release (V01.01.05–08) of tropical tropospheric ozone column data (TrOC). Derived with the Convective Cloud Differential (CCD) method, TROPOMI daily TrOC data represent the three-day moving mean ozone column between surface and 270 hpa under clear sky conditions gridded at 0.5° latitude by 1° longitude resolution. Comparisons to almost two years of co-located SHADOZ ozonesonde and satellite data (Aura OMI and MetOp-B GOME-2) conclude to TROPOMI biases between −0.1 and +2.3 DU (< +13 %) when averaged over the tropical belt. The field of the bias is essentially uniform in space (deviations < 1 DU) and stable in time at the 1.5–2.5 DU level. However, the record is still fairly short and continued monitoring will be key to clarify whether observed patterns and stability persist, alter behaviour or disappear. Biases are partially due to TROPOMI and the reference data records themselves, but they can also be linked to systematic effects of the non perfect co-locations. Random uncertainty due to co-location mismatch contributes considerably to the 2.6–4.6 DU (~14–23 %) statistical dispersion observed in the difference time series. We circumvent part of this problem by employing the triple co-location analysis technique and infer that TROPOMI single-measurement precision is better than 1.5–2.5 DU (~8–13 %), in line with uncertainty estimates reported in the data files. Hence, the TROPOMI precision is judged to be 20–25 % better than for its predecessors OMI and GOME-2B, while sampling at four times better spatial resolution and almost twice better temporal resolution. Using TROPOMI tropospheric ozone columns at maximal resolution nevertheless requires consideration of correlated errors at small scales of up to 5 DU due to the inevitable interplay of satellite orbit and cloud coverage. Two particular types of sampling error are investigated and we suggest how these can be identified or remedied. Our study confirms that major known geophysical patterns and signals of the tropical tropospheric ozone field are imprinted in TROPOMI's two-year data record. These include the permanent zonal wave-one pattern, the pervasive annual and semiannual cycles, the high levels of ozone due to biomass burning around the Atlantic basin, and enhanced convective activity cycles associated with the Madden-Julian Oscillation over the Indo-Pacific warm pool. A quasi-periodic signal of 1–2 weeks and 3–5 DU amplitude in TrOC time series, especially at low latitudes, is reminiscent of Kelvin wave activity. TROPOMI's combination of higher precision and higher resolution reveal details of these patterns and the processes involved, at considerably smaller spatial and temporal scales and with more complete coverage than contemporary satellite sounders. If the accuracy of future TROPOMI data proves to remain stable with time, these hold great potential to be included in Climate Data Records, as well as serve as a travelling standard to interconnect the upcoming constellation of air quality satellites in geostationary and low Earth orbits.

Daan Hubert et al.

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Short summary
We assess the first two years of TROPOMI tropical tropospheric ozone column data. Comparisons to reference measurements by ozonesonde and satellite sensors show that TROPOMI bias (−0.1 to +2.3 DU) and precision (1.5 to 2.5 DU) meet mission requirements. Potential causes of bias and its spatio-temporal structure are discussed, as well as ways to identify sampling errors. The analysis of the known geophysical patterns demonstrates the improved performance of TROPOMI with respect to predecessors.
We assess the first two years of TROPOMI tropical tropospheric ozone column data. Comparisons to...
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