Impact of using different ozone cross sections on ozone profile retrievals from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements

Liu, X.; Chance, K.; Sioris, Christopher E.; Kurosu, Thomas P.

doi:10.5194/acp-7-3571-2007

Cited by 57 publications

(54 citation statements)

References 19 publications

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“…Original research by Liu et al (2007) found that the choice of the BDM ozone x-section would change GOME retrieved total ozone up to 12 %. The application of the BDM data for ozone retrieval also improved the spectral residuals of the fit to the satellite measurements.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity of Dobson and Brewer Umkehr ozone profile retrievals to ozone cross-sections and stray light effects

et al. 2011

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Abstract. Remote sounding methods are used to derive ozone profile and column information from various groundbased and satellite measurements. Vertical ozone profiles measured in Dobson units (DU) are currently retrieved based on laboratory measurements of the ozone absorption crosssection spectrum between 270 and 400 nm published in 1985 by Bass and Paur (BP). Recently, the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) proposed using the set of ozone crosssection measurements made at the Daumont laboratory in 1992 (BDM) for revising the Aura Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME) satellite ozone profiles and total ozone column retrievals. Dobson Umkehr zenith sky data have been collected by NOAA ground-based stations at Boulder, CO (BDR) and Mauna Loa Observatory, HI (MLO) since the 1980s. The UMK04 algorithm is based on the BP ozone cross-section data. It is currently used for all Dobson Umkehr data processing submitted to the World Ozone and Ultraviolet radiation Data Centre (WOUDC) under the Global Atmosphere Watch (GAW) program of the World Meteorological Organization (WMO). Ozone profiles are also retrieved from measurements by the Mark IV Brewers operated by the NOAA-EPA Brewer Spectrophotometer UV and Ozone Network (NEUBrew) using a modified UMK04 algorithm (O3BUmkehr v.2.6, Martin Stanek). This paper describes the sensitivity of the Umkehr retrievals with respect to the proposed ozone cross-section changes. It is found that the Correspondence to: I. Petropavlovskikh (irina.petro@noaa.gov) ozone cross-section choice only minimally (within the retrieval accuracy) affects the Dobson and the Brewer Umkehr retrievals. On the other hand, significantly larger errors were found in the MLO and Boulder Umkehr ozone data (−8 and +5 % bias in stratosphere and troposphere respectively) when the out-of-band (OOB) stray light contribution to the Umkehr measurement is not taken into account (correction is currently not included in the UMK04). The vertical distribution of OOB effect in the retrieved profile can be related to the local ozone climatology, instrument degradation, and optical characteristics of the instrument. Nonetheless, recurring OOB errors do not contribute to the long-term ozone trends.

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Section: Discussionmentioning

confidence: 99%

Sensitivity of Dobson and Brewer Umkehr ozone profile retrievals to ozone cross-sections and stray light effects

et al. 2011

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“…The OMI random noise errors reported in the level 1b radiance data are used to construct the measurement error covariance matrix. Ozone cross sections are from Brion-Daumont-Malicet (BDM) (Brion et al, 1993), which was recommended for use in ozone profile retrievals from UV measurements by Liu et al (2007) and Liu et al (2013). Despite these similarities, the two algorithms have many different implementation details, including state and a priori components, radiative transfer model calculations, and radiometric and wavelength calibration treatments.…”

Section: Ozone Monitoring Instrument (Omi) and Omi Ozone Algorithmsmentioning

confidence: 99%

Validation of OMI total ozone retrievals from the SAO ozone profile algorithm and three operational algorithms with Brewer measurements

et al. 2015

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Abstract. The accuracy of total ozone computed from the Smithsonian Astrophysical Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE) applied to the Ozone Monitoring Instrument (OMI) is assessed through comparisons with ground-based Brewer spectrometer measurements from 2005 to 2008. We also compare the three OMI operational ozone products, derived from the NASA Total Ozone Mapping Spectrometer (TOMS) algorithm, the KNMI (Royal Netherlands Meteorological Institute) differential optical absorption spectroscopy (DOAS) algorithm, and KNMI's Optimal Estimation (KOE) algorithm. The best agreement is observed between SAO and Brewer, with a mean difference of within 1 % at most individual stations. The KNMI OE algorithm systematically overestimates Brewer total ozone by 2 % at low and mid-latitudes and 5 % at high latitudes while the TOMS and DOAS algorithms underestimate it by ∼ 1.65 % on average. Standard deviations of ∼ 1.8 % are calculated for both SOE and TOMS, but DOAS and KOE have higher values of 2.2 % and 2.6 %, respectively. The stability of the SOE algorithm is found to have insignificant dependence on viewing geometry, cloud parameters, or total ozone column. In comparison, the KOEBrewer differences are significantly correlated with solar and viewing zenith angles and show significant deviations depending on cloud parameters and total ozone amount. The TOMS algorithm exhibits similar stability to SOE with respect to viewing geometry and total column ozone, but has stronger cloud parameter dependence. The dependence of DOAS on observational geometry and geophysical conditions is marginal compared to KOE, but is distinct compared to the SOE and TOMS algorithms. Comparisons of all four OMI products with Brewer show no apparent long-term drift, but seasonal features are evident, especially for KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm performance cannot be sufficiently explained by the use of soft calibration (in SOE) and the use of different a priori error covariance matrices; however, other algorithm details cause fitting residuals larger by a factor of 2-3 for KOE.

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“…HITRAN 2008 also contains polynomial coefficients (BP HITRAN ); however, a few corrections were made on the original BP data: air-vacuum wavelength conversion according to Edlen's equation (Edlen, 1966) and wavelength shift. Using original BMD data at four temperatures (218, 228, 243, and 295 K), Liu et al (2007) derived polynomial coefficients for temperature dependence for vacuum wavelength scale (BMD calc ), making possible the interpolation/extrapolation of the cross-sections to any given temperature. More details on the polynomial temperature parameterization of the cross-sections can be found, for example, in , and in our companion paper: Serdyuchenko et al (2014).…”

Section: Spectral Region 323-340 Nmmentioning

confidence: 99%

High spectral resolution ozone absorption cross-sections – Part 1: Measurements, data analysis and comparison with previous measurements around 293 K

et al. 2014

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Abstract. In this paper we discuss the methodology of taking broadband relative and absolute measurements of ozone cross-sections including uncertainty budget, experimental set-ups, and methods for data analysis. We report on new ozone absorption cross-section measurements in the solar spectral region using a combination of Fourier transform and echelle spectrometers. The new cross-sections cover the spectral range 213-1100 nm at a spectral resolution of 0.02-0.06 nm in the UV-visible and 0.12-0.24 nm in the IR at eleven temperatures from 193 to 293 K in steps of 10 K. The absolute accuracy is better than three percent for most parts of the spectral region and wavelength calibration accuracy is better than 0.005 nm.The new room temperature cross-section data are compared in detail with previously available literature data. The temperature dependence of our cross-sections is described in a companion paper (Serdyuchenko et al., 2014).

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Impact of using different ozone cross sections on ozone profile retrievals from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements

Cited by 57 publications

References 19 publications

Sensitivity of Dobson and Brewer Umkehr ozone profile retrievals to ozone cross-sections and stray light effects

Sensitivity of Dobson and Brewer Umkehr ozone profile retrievals to ozone cross-sections and stray light effects

Validation of OMI total ozone retrievals from the SAO ozone profile algorithm and three operational algorithms with Brewer measurements

High spectral resolution ozone absorption cross-sections – Part 1: Measurements, data analysis and comparison with previous measurements around 293 K

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