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Volume 9, issue 8 | Copyright

Special issue: Twenty-five years of operations of the Network for the Detection...

Atmos. Meas. Tech., 9, 4051-4078, 2016
https://doi.org/10.5194/amt-9-4051-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 25 Aug 2016

Research article | 25 Aug 2016

Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 2: Ozone DIAL uncertainty budget

Thierry Leblanc1, Robert J. Sica2, Joanna A. E. van Gijsel3, Sophie Godin-Beekmann4, Alexander Haefele5, Thomas Trickl6, Guillaume Payen7, and Gianluigi Liberti8 Thierry Leblanc et al.
  • 1Jet Propulsion Laboratory, California Institute of Technology, Wrightwood, CA 92397, USA
  • 2Department of Physics and Astronomy, The University of Western Ontario, London, Canada
  • 3Royal Netherlands Meteorological Institute (KNMI), Bilthoven, the Netherlands
  • 4LATMOS-IPSL, CNRS-INSU, Paris, France
  • 5Meteoswiss, Payerne, Switzerland
  • 6Karlsruher Institut für Technologie, IMK-IFU, Garmisch-Partenkirchen, Germany
  • 7Observatoire des Sciences de l'Univers de La Réunion, CNRS and Université de la Réunion (UMS3365), Saint Denis de la Réunion, France
  • 8ISAC-CNR, Via Fosso del Cavaliere 100, 00133 Rome, Italy

Abstract. A standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One essential aspect of the proposed approach is the propagation in parallel of all independent uncertainty components through the data processing chain before they are combined together to form the ozone combined standard uncertainty.

The independent uncertainty components contributing to the overall budget include random noise associated with signal detection, uncertainty due to saturation correction, background noise extraction, the absorption cross sections of O3, NO2, SO2, and O2, the molecular extinction cross sections, and the number densities of the air, NO2, and SO2. The expression of the individual uncertainty components and their step-by-step propagation through the ozone differential absorption lidar (DIAL) processing chain are thoroughly estimated. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which requires knowledge of the covariance matrix when the lidar signal is vertically filtered. In addition, the covariance terms must be taken into account if the same detection hardware is shared by the lidar receiver channels at the absorbed and non-absorbed wavelengths.

The ozone uncertainty budget is presented as much as possible in a generic form (i.e., as a function of instrument performance and wavelength) so that all NDACC ozone DIAL investigators across the network can estimate, for their own instrument and in a straightforward manner, the expected impact of each reviewed uncertainty component. In addition, two actual examples of full uncertainty budget are provided, using nighttime measurements from the tropospheric ozone DIAL located at the Jet Propulsion Laboratory (JPL) Table Mountain Facility, California, and nighttime measurements from the JPL stratospheric ozone DIAL located at Mauna Loa Observatory, Hawai'i.

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This article proposes a standardized approach for the treatment of uncertainty in the ozone differential absorption lidar data processing algorithms. The recommendations are designed to be used homogeneously across large atmospheric observation networks such as NDACC, and allow a clear understanding of the uncertainty budget of multiple lidar datasets for a large spectrum of ozone-related science applications (e.g., climatology, long-term trends, air quality).
This article proposes a standardized approach for the treatment of uncertainty in the ozone...
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