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Discussion papers | Copyright
https://doi.org/10.5194/amt-2018-200
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 16 Aug 2018

Research article | 16 Aug 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Improving algorithms and uncertainty estimates for satellite NO2 retrievals: Results from the Quality Assurance for Essential Climate Variables (QA4ECV) project

K. Folkert Boersma1,2, Henk J. Eskes1, Andreas Richter3, Isabelle De Smedt4, Alba Lorente2, Steffen Beirle5, Jos H. G. M. van Geffen1, Marina Zara1, Enno Peters3, Michel Van Roozendael4, Thomas Wagner5, Joannes D. Maasakkers6, Ronald J. van der A1, Joanne Nightingale7, Anne De Rudder4, Hitoshi Irie8, Gaia Pinardi4, Jean-Christopher Lambert4, and Steven Compernolle4 K. Folkert Boersma et al.
  • 1Royal Netherlands Meteorological Institute, Satellite Observations department, the Netherlands
  • 2Wageningen University, Meteorology and Air Quality Group, Wageningen, the Netherlands
  • 3Institute of Environmental Physics (IUP-UB), University of Bremen, Bremen, Germany
  • 4Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
  • 5Max-Planck Institute for Chemistry (MPI-C), Mainz, Germany
  • 6Harvard University, Cambridge, Massachusetts, USA
  • 7National Physics Laboratory (NPL), Teddington, UK
  • 8Center for Environmental Remote Sensing (CEReS), Chiba University, Chiba, Japan

Abstract. Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities on the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1°×1° TM5-MP data assimilation scheme to estimate the stratospheric background, and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm on the most actual level-1 data sets to produce a complete 22-year data record that includes GOME (1995-2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40% over polluted scenes. First validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai’an, China in June 2006 suggests little bias (−27thinsp;%) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

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Data sets

QA4ECV NO2 tropospheric and stratospheric vertical column data from OMI (Version 1.1) K. F. Boersma, H. Eskes, A. Richter, I. De Smedt, A. Lorente, S. Beirle, J. Van Geffen, E. Peters, M. Van Roozendael, and T. Wagner https://doi.org/10.21944/qa4ecv-no2-omi-v1.1

QA4ECV NO2 tropospheric and stratospheric vertical column data from GOME-2A (Version 1.1) K. F. Boersma, H. Eskes, A. Richter, I. De Smedt, A. Lorente, S. Beirle, J. Van Geffen, E. Peters, M. Van Roozendael, and T. Wagner https://doi.org/10.21944/qa4ecv-no2-gome2a-v1.1

QA4ECV NO2 tropospheric and stratospheric vertical column data from SCIAMACHY (Version 1.1) K. F. Boersma, H. Eskes, A. Richter, I. De Smedt, A. Lorente, S. Beirle, J. Van Geffen, E. Peters, M. Van Roozendael, and T. Wagner https://doi.org/10.21944/qa4ecv-no2-scia-v1.1

QA4ECV NO2 tropospheric and stratospheric vertical column data from GOME (Version 1.1) K. F. Boersma, H. Eskes, A. Richter, I. De Smedt, A. Lorente, S. Beirle, J. Van Geffen, E. Peters, M. Van Roozendael, and T. Wagner https://doi.org/10.21944/qa4ecv-no2-gome-v1.1

K. Folkert Boersma et al.
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This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2) pollution measurements from different satellite instruments. Our work helps ensure that climate data is of sufficient quality to draw reliable conclusions and shape decisions. It shows how dedicated intercomparisons of retrieval substeps have led to improved NO2 measurements from the GOME, SCIAMACHY, GOME-2(A), and OMI sensors, and how quality assurance of the new data product is achieved.
This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2)...
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