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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 7 | Copyright

Special issue: TROPOMI on Sentinel-5 Precursor: data products and...

Atmos. Meas. Tech., 9, 2753-2779, 2016
https://doi.org/10.5194/amt-9-2753-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 04 Jul 2016

Research article | 04 Jul 2016

The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution

Steffen Beirle1, Christoph Hörmann1, Patrick Jöckel2, Song Liu3, Marloes Penning de Vries1, Andrea Pozzer1, Holger Sihler1, Pieter Valks3, and Thomas Wagner1 Steffen Beirle et al.
  • 1Max Planck Institute for Chemistry, Mainz, Germany
  • 2Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 3Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany

Abstract. The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1–0.2×1015moleculescm−2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.

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