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Discussion papers | Copyright
https://doi.org/10.5194/essd-2018-56
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Review article 04 May 2018

Review article | 04 May 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

An updated version of a gap-free monthly mean zonal mean ozone database

Birgit Hassler1,2, Stefanie Kremser1, Greg E. Bodeker1, Jared Lewis1, Kage Nesbit1, Sean M. Davis3,4, Martyn P. Chipperfield5,6, Sandip S. Dhomse5,6, and Martin Dameris2 Birgit Hassler et al.
  • 1Bodeker Scientific, 42 Russell Street, Alexandra, 9320, New Zealand
  • 2Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 3Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • 4NOAA Earth System Research Laboratory, Boulder, CO, USA
  • 5School of Earth and Environment, University of Leeds, Leeds, UK
  • 6National Centre for Earth Observation, University of Leeds, Leeds, UK

Abstract. An updated and improved version of a global, vertically resolved, monthly mean zonal mean ozone database has been calculated – hereafter referred to as the BSVertOzone database. Like its predecessor, it combines measurements from several satellite-based instruments and ozone profile measurements from the global ozonesonde network. Monthly mean zonal mean ozone concentrations in mixing ratio and number density are provided in 5° latitude bins, spanning 70 altitude levels (1 to 70km), or 70 pressure levels that are approximately 1km apart (878.4hPa to 0.046hPa). Different data sets or Tiers are provided: Tier 0 is based only on the available measurements and therefore does not completely cover the whole globe or the full vertical range uniformly; the Tier 0.5 monthly mean zonal means are calculated as a filled version of the Tier 0 database where missing monthly mean zonal mean values are estimated from correlations against a total column ozone database. The Tier 0.5 data set includes the full range of measurement variability and is created as an intermediate step for the calculation of the Tier 1 data where a least squares regression model is used to attribute variability to various known forcing factors for ozone. Regression model fit coefficients are expanded in Fourier series and Legendre polynomials (to account for seasonality and latitudinal structure, respectively). Four different combinations of contributions from selected regression model basis functions result in four different Tier 1 data sets that can be used for comparisons with chemistry-climate model simulations that do not exhibit the same unforced variability as reality (unless they are nudged towards reanalyses). Compared to previous versions of the database, this update includes additional satellite data sources and ozonesonde measurements to extend the database period to 2016. Additional improvements over the previous version of the database include: (i) Adjustments of measurements to account for biases and drifts between different data sources (using a chemistry-transport model simulation as a transfer standard), (ii) a more objective way to determine the optimum number of Fourier and Legendre expansions for the basis function fit coefficients, and (iii) the derivation of methodological and measurement uncertainties on each database value are traced through all data modification steps. Comparisons with the ozone database from SWOOSH (Stratospheric Water and OzOne Satellite Homogenized data set) show good agreement in many regions of the globe. Minor differences are caused by different bias adjustment procedures for the two databases. However, compared to SWOOSH, BSVertOzone additionally covers the troposphere. Version 1.0 of BSVertOzone is publicly available at http://doi.org/10.5281/zenodo.1217184.

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Birgit Hassler et al.
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Birgit Hassler et al.
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BSVerticalOzone database B. Hassler, S. Kremser, G. Bodeker, J. Lewis, K. Nesbit, S. Davis, M. Chipperfield, S. Dhomse, and M. Dameris https://doi.org/10.5281/zenodo.1217184

Birgit Hassler et al.
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