SAGE version 7.0 algorithm: application to SAGE II

Damadeo, Robert; Zawodny, J. M.; Thomason, L. W.; Iyer, N. V.

doi:10.5194/amt-6-3539-2013

Cited by 133 publications

(182 citation statements)

References 33 publications

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“…Although modeled ozone does show some biases against satellite data, there are significant biases in the observational data itself. Detailed analysis of the differences between SAGE v6.2 and SAGE v7.0 are discussed in Damadeo et al [2013]. The number of profiles used to calculate tropical monthly mean and calculated monthly means using SAGE v6.2 and v7 is also shown in Figures S1 and S2 in the supporting information.…”

Section: Resultsmentioning

confidence: 99%

On the ambiguous nature of the 11 year solar cycle signal in upper stratospheric ozone

Dhomse

Chipperfield

Damadeo

et al. 2016

Geophysical Research Letters

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Up to now our understanding of the 11 year ozone solar cycle signal (SCS) in the upper stratosphere has been largely based on the Stratospheric Aerosol and Gas Experiment (SAGE) II (v6.2) data record, which indicated a large positive signal which could not be reproduced by models, calling into question our understanding of the chemistry of the upper stratosphere. Here we present an analysis of new v7.0 SAGE II data which shows a smaller upper stratosphere ozone SCS, due to a more realistic ozone‐temperature anticorrelation. New simulations from a state‐of‐art 3‐D chemical transport model show a small SCS in the upper stratosphere, which is in agreement with SAGE v7.0 data and the shorter Halogen Occultation Experiment and Microwave Limb Sounder records. However, despite these improvements in the SAGE II data, there are still large uncertainties in current observational and meteorological reanalysis data sets, so accurate quantification of the influence of solar flux variability on the climate system remains an open scientific question.

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Section: Resultsmentioning

confidence: 99%

On the ambiguous nature of the 11 year solar cycle signal in upper stratospheric ozone

Dhomse

Chipperfield

Damadeo

et al. 2016

Geophysical Research Letters

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“…With the analysis of SD-WACCM output, this difference is found not due to the difference in measurement locations or times among the data sets. The retrieval procedure in SAGE II has been greatly updated in SAGE II version 7 data (Damadeo et al, 2013). We have so far no clear answer to the difference; there may be several possibilities as discussed in the following.…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

et al. 2015

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Abstract. This paper contains a comprehensive investigation of the sunset-sunrise difference (SSD, i.e., the sunsetminus-sunrise value) of the ozone mixing ratio in the latitude range of 10 • S-10 • N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment-Fourier transform spectrometer (ACE-FTS). The SSD was negative at altitudes of 20-30 km (−0.1 ppmv at 25 km) and positive at 30-50 km (+0.2 ppmv at 40-45 km) for HALOE and ACE-FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was 2 times larger than those derived from the other data sets. On the basis of an analysis of data from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and a nudged chemical transport model (the specified dynamics version of the Whole Atmosphere Community Climate Model: SD-WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All data sets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March-April and September-October. Based on an analysis of SD-WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.

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“…In late 2012, an improved and updated version of the SAGE II data set was released (version 7.0; Damadeo et al, 2013). This replaced the version 6.2 data set that was used in BDBP v1.1.0.6.…”

Section: Observation-based Data Sourcesmentioning

confidence: 99%

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

Haßler

Kremser

Bodeker

et al. 2018

Earth Syst. Sci. Data

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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 (Bodeker Scientific Vertical Ozone) 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 70 km), or 70 pressure levels that are approximately 1 km apart (878.4 to 0.046 hPa). 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 (TCO) 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 (CCM) 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 the following: (i) adjustments of measurements to account for biases and drifts between different data sources (using a chemistry-transport model, CTM, 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 https://doi.org/http://doi.org/10

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SAGE version 7.0 algorithm: application to SAGE II

Cited by 133 publications

References 33 publications

On the ambiguous nature of the 11 year solar cycle signal in upper stratospheric ozone

On the ambiguous nature of the 11 year solar cycle signal in upper stratospheric ozone

Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

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

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