Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
  • CiteScore value: 3.71 CiteScore
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
Volume 11, issue 4 | Copyright

Special issue: Quadrennial Ozone Symposium 2016 – Status and trends...

Atmos. Meas. Tech., 11, 2135-2149, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 13 Apr 2018

Research article | 13 Apr 2018

Retrieval of ozone profiles from OMPS limb scattering observations

Carlo Arosio1, Alexei Rozanov1, Elizaveta Malinina1, Kai-Uwe Eichmann1, Thomas von Clarmann2, and John P. Burrows1 Carlo Arosio et al.
  • 1Institute of Environmental Physics, University of Bremen, Bremen, Germany
  • 2Karlsruhe Institute of Technology, Karlsruhe, Germany

Abstract. This study describes a retrieval algorithm developed at the University of Bremen to obtain vertical profiles of ozone from limb observations performed by the Ozone Mapper and Profiler Suite (OMPS). This algorithm is based on the technique originally developed for use with data from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument. As both instruments make limb measurements of the scattered solar radiation in the ultraviolet (UV) and visible (Vis) spectral ranges, an underlying objective of the study is to obtain consolidated and consistent ozone profiles from the two satellites and to produce a combined data set. The retrieval algorithm uses radiances in the UV and Vis wavelength ranges normalized to the radiance at an upper tangent height to obtain ozone concentrations in the altitude range of 12–60km. Measurements at altitudes contaminated by clouds in the instrument field of view are identified and filtered out. An independent aerosol retrieval is performed beforehand and its results are used to account for the stratospheric aerosol load in the ozone inversion. The typical vertical resolution of the retrieved profiles varies from  ∼ 2.5km at lower altitudes ( < 30km) to  ∼ 1.5km (about 45km) and becomes coarser at upper altitudes. The retrieval errors resulting from the measurement noise are estimated to be 1–4% above 25km, increasing to 10–30% in the upper troposphere. OMPS data are processed for the whole of 2016. The results are compared with the NASA product and validated against profiles derived from passive satellite observations or measured in situ by balloon-borne sondes. Between 20 and 60km, OMPS ozone profiles typically agree with data from the Microwave Limb Sounder (MLS) v4.2 within 5–10%, whereas in the lower altitude range the bias becomes larger, especially in the tropics. The comparison of OMPS profiles with ozonesonde measurements shows differences within ±5% between 13 and 30km at northern middle and high latitudes. At southern middle and high latitudes, an agreement within 5–7% is also achieved in the same altitude range. An unexpected bias of approximately 10–20% is detected in the lower tropical stratosphere. The processing of the 2013 data set using the same retrieval settings and its validation against ozonesondes reveals a much smaller bias; a possible reason for this behaviour is discussed.

Publications Copernicus
Special issue
Short summary
This paper describes the development of a retrieval algorithm at the University of Bremen which derives stratospheric ozone profiles from limb observations performed by the OMPS satellite instrument. Here we present the implementation of the algorithm and the validation of our results (1 year of data against independent satellite and ground-based measurements). Good agreement is generally found between 20 and 55 km, mostly within 10 % at all latitudes.
This paper describes the development of a retrieval algorithm at the University of Bremen which...