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

Steven Compernolle*, Tijl Verhoelst, Gaia Pinardi, Jose Granville, Daan Hubert, Arno Keppens, Sander Niemeijer, Bruno Rino, Alkis Bais, Steffen Beirle, Folkert Boersma, John P. Burrows, Isabelle De Smedt, Henk Eskes, Florence Goutail, Francois Hendrick, Alba Lorente, Andrea Pazmino, Ankie Piters, Enno PetersJean Pierre Pommereau, Julia Remmers, Andreas Richter, Jos Van Geffen, Michel Van Roozendael, Thomas Wagner, Jean Christopher Lambert

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

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) zenithscattered 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 ZSLDOAS 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.

Original languageEnglish
Pages (from-to)8017-8045
Number of pages29
JournalAtmospheric Chemistry and Physics
Volume20
Issue number13
DOIs
Publication statusPublished - 10 Jul 2020

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