The Ultraviolet Cross-Sections of Ozone: I. The Measurements

Bass, Arnold M.; Paur, Richard J.

doi:10.1007/978-94-009-5313-0_120

Cited by 309 publications

(300 citation statements)

References 2 publications

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“…The algorithm is rather insensitive to calibration error that does not vary with wavelength, but it is more sensitive to wavelength-relative error (Bhartia and Wellemeyer, 2002). The TOMS algorithm uses ozone crosssection data based on Bass and Paur (1985). OMTO3 total ozone measurements largely rely on OMI's pre-launch radiometric calibration at nadir described by Dobber et al (2006) and validated by Jaross and Warner (2008).…”

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

confidence: 99%

“…Absorption coefficients based on Bass and Paur (1985) data are used in the standard Brewer algorithm. In addition, the standard Brewer algorithm does not consider the temperature dependence of ozone cross sections and instead uses a fixed temperature of −45 • C. Several studies have evaluated the effects of using newer high-resolution ozone cross-section data sets and accounting for temperature dependence on Brewer total ozone retrievals and their consistency with retrievals from Dobson spectrometers (Fragkos et al, 2013;Redonas et al, 2014).…”

Section: Woudc Brewer Total Ozone Datamentioning

confidence: 99%

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

confidence: 99%

Section: Woudc Brewer Total Ozone Datamentioning

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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“…Comparison of the observed spectrum with one measured in the laboratory allows the determination of total column ozone in the atmosphere. The results reported in this work are referenced to the laboratory ozone absorption coefficient measurements of Bass and Paur (1985) and Paur and Bass (1985). Moonlight is directed into the Brewer instrument by the same pointing optics used standard deviation of the individual observations about the mean is taken as an estimate of the precision of the measurement.…”

Section: Methods Of Measurementmentioning

confidence: 99%

Measurements of arctic total ozone during the polar winter

et al. 1990

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“…The model is set up to use the ozone cross-section as described by Bass and Paur (1985), but can also use the more recent ozone cross-section studies by Daumont et al (1992) and Gorshelev et al (2014). However, the effect of the ozone cross-section used in C-pair Umkehr retrieval algorithms was studied by Petropavlovskikh et al (2011) and found to have minimal effect.…”

Section: Radiative Transfer Modelmentioning

confidence: 99%

A new Dobson Umkehr ozone profile retrieval method optimising information content and resolution

et al. 2015

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Abstract. The standard Dobson Umkehr methodology to retrieve coarse-resolution ozone profiles used by the National Oceanographic and Atmospheric Administration uses designated solar zenith angles (SZAs). However, some information may be lost if measurements lie outside the designated SZA range (between 60 • and 90 • ), or do not conform to the fitting technique. Also, while Umkehr measurements can be taken using multiple wavelength pairs (A, C and D), past retrieval methods have focused on a single pair (C). Here we present an Umkehr inversion method that uses measurements at all SZAs (termed operational) and all wavelength pairs. (Although, we caution direct comparison to other algorithms.)Information content for a Melbourne, Australia (38 • S, 145 • E) Umkehr measurement case study from 28 January 1994, with SZA range similar to that designated in previous algorithms is shown. When comparing the typical single wavelength pair with designated SZAs to the operational measurements, the total degrees of freedom (independent pieces of information) increases from 3.1 to 3.4, with the majority of the information gain originating from Umkehr layers 2 + 3 and 4 (10-20 km and 25-30 km respectively). In addition to this, using all available wavelength pairs increases the total degrees of freedom to 5.2, with the most significant increases in Umkehr layers 2 + 3 to 7 and 9+ (10-40 and 45-80 km). Investigating a case from 13 April 1970 where the measurements extend beyond the 90 • SZA range gives further information gain, with total degrees of freedom extending to 6.5. Similar increases are seen in the information content. Comparing the retrieved Melbourne Umkehr time series with ozonesondes shows excellent agreement in layers 2 + 3 and 4 (10-20 and 25-30 km) for both C and A + C + D-pairs. Retrievals in layers 5 and 6 (25-30 and 30-35 km) consistently show lower ozone partial column compared to ozonesondes. This is likely due to stray light effects that are not accounted for in the forward model, and under represented stratospheric aerosol.

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The Ultraviolet Cross-Sections of Ozone: I. The Measurements

Cited by 309 publications

References 2 publications

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

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

Measurements of arctic total ozone during the polar winter

A new Dobson Umkehr ozone profile retrieval method optimising information content and resolution

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