Evaluation of Global Ozone Monitoring Experiment (GOME) ozone profiles from nine different algorithms

Abstract

[1] An evaluation is made of ozone profiles retrieved from measurements of the nadir-viewing Global Ozone Monitoring Experiment (GOME) instrument. Currently, four different approaches are used to retrieve ozone profile information from GOME measurements, which differ in the use of external information and a priori constraints. In total nine different algorithms will be evaluated exploiting the optimal estimation (Royal Netherlands Meteorological Institute, Rutherford Appleton Laboratory, University of Bremen, National Oceanic and Atmospheric Administration, Smithsonian Astrophysical Observatory), Phillips-Tikhonov regularization (Space Research Organization Netherlands), neural network (Center for Solar Energy and Hydrogen Research, Tor Vergata University), and data assimilation (German Aerospace Center) approaches. Analysis tools are used to interpret data sets that provide averaging kernels. In the interpretation of these data, the focus is on the vertical resolution, the indicative altitude of the retrieved value, and the fraction of a priori information. The evaluation is completed with a comparison of the results to lidar data from the Network for Detection of Stratospheric Change stations in Andoya (Norway), Observatoire Haute Provence (France), Mauna Loa (Hawaii), Lauder (New Zealand), and Dumont d'Urville (Antarctic) for the years 1997-1999. In total, the comparison involves nearly 1000 ozone profiles and allows the analysis of GOME data measured in different global regions and hence observational circumstances. The main conclusion of this paper is that unambiguous information on the ozone profile can at best be retrieved in the altitude range 15-48 km with a vertical resolution of 10 to 15 km, precision of 5-10%, and a bias up to 5% or 20% depending on the success of recalibration of the input spectra. The sensitivity of retrievals to ozone at lower altitudes varies from scheme to scheme and includes significant influence from a priori assumptions.

Past changes in the vertical distribution of ozone – Part 1: Measurement techniques, uncertainties and availability

“…As for SBUV, Optimal Estimation techniques (Rodgers, 2000) are used for the retrievals. GOME ozone profiles were extensively analyzed by Meijer et al (2006) and when the OMI measurements became available these were validated by Kroon et al (2011).…”

Ozone profile retrievals from the Ozone Monitoring Instrument

“…Over the years, several groups, have developed physically based retrieval algorithms to retrieve ozone profiles from GOME radiances (Munro et al, 1998;Hoogen et al, 1999;Hasekamp and Landgraf, 2001;van der A et al, 2002;Liu et al, 2005). Meijer et al (2006) evaluated ozone profiles retrieved from these algorithms and concluded that, though ozone profiles can be retrieved from GOME with better information content in the lower stratosphere than that from Solar Backscatter Ultraviolet (SBUV) instruments, they were not able to demonstrate robust determination of tropospheric ozone.…”

Improvement of OMI ozone profile retrievals in the upper troposphere and lower stratosphere by the use of a tropopause-based ozone profile climatology

“…Because these instruments measure BUV radiances only at 12 discrete wavelength bands in the range of 256-340 nm, the information on ozone vertical distribution is limited to 20-50 km (Bhartia et al, 1996). With the launch of UV/visible spectrometers such as the Global Ozone Monitoring Experiment (GOME) (ESA, 1995), which take BUV radiance spectra at moderate spectral resolution, the retrieval of vertical ozone profiles can be extended down to the troposphere (Chance et al, 1997;Meijer et al, 2006 and references therein). Liu et al (2005) developed an optimal estimation (OE)-based algorithm to retrieve ozone profiles including tropospheric ozone from GOME BUV radiance spectra.…”