GOMOS data characterisation and error estimation

Tamminen, J.; Kyrölä, E.; Sofieva, Viktoria; Laine, Marko; Bertaux, Jean-Loup; Hauchecorne, Alain; Dalaudier, Francis; Fussen, D.; Vanhellemont, F.; Fanton-d'Andon, O.; Barrot, G.; Mangin, A.; Guirlet, M.; Blanot, Laurent; Fehr, T.; Miguel, L. Saavedra de; Fraïssé, R.

doi:10.5194/acp-10-9505-2010

Cited by 49 publications

(50 citation statements)

References 30 publications

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“…GOMOS has performed about 150-200 nighttime occultations per day with global coverage. Typical examples of GOMOS data coverage and distribution over the globe are shown, for example, in Bertaux et al (2010), Kyrölä et al (2010), Sofieva et al (2013), and Tamminen et al (2010). The vertical resolution (including the smoothing properties of the inversion) of GOMOS ozone profiles is 2 km below 30 km and 3 km above 40 km; it is the same for all occultations.…”

Section: F Sofieva Et Al: Validation Of Gomos Ozone Precision Esmentioning

confidence: 94%

“…Other GOMOS self-collocations (less than 30 per year) are for different stars in successive orbits (Guirlet et al, ) in years 2002(Guirlet et al, -2004 The estimated retrieval uncertainty for GOMOS ozone is small in the stratosphere; for very bright stars it is ∼ 0.5-2 % (Sofieva et al, 2009;Tamminen et al, 2010). For an experimental estimation of precision in such occultations by the Fioletov method, a very large number of collocations with measurements from another instrument is needed, even in regions of low natural variability (Appendix B).…”

Section: Specifics Of Gomos Measurements and Challenges For Precisionmentioning

confidence: 99%

“…The residual scintillation error depends on the obliquity of occultation; it vanishes for vertical (in-orbital-plane) occultations. Both the instrumental noise and the residual scintillation error are then propagated through the inversion (for details, see Kyrölä et al, 2010;Sofieva et al, 2010;Tamminen et al, 2010), and the uncertainties of the retrieved profiles are given by the corresponding covariance matrices. The square roots of their diagonal elements are often referred to (also in this paper) as precision estimates.…”

Section: Outlines Of Gomos Precision Derivation and Characterization mentioning

confidence: 99%

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Validation of GOMOS ozone precision estimates in the stratosphere

et al. 2014

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Abstract. Accurate information about uncertainties is required in nearly all data analyses, e.g., inter-comparisons, data assimilation, combined use. Validation of precision estimates (viz., the random component of estimated uncertainty) is important for remote sensing measurements, which provide the information about atmospheric parameters by solving an inverse problem. For the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, this is a real challenge, due to the dependence of the signal-to-noise ratio (and thus precision estimates) on stellar properties, small number of self-collocated measurements, and growing noise as a function of time due to instrument aging. The estimated ozone uncertainties are small in the stratosphere for bright star occultations, which complicates validation of precision values, given the natural ozone variability.In this paper, we discuss different methods for geophysical validation of precision estimates and their applicability to GOMOS data. We propose a simple method for validation of GOMOS precision estimates for ozone in the stratosphere. This method is based on comparisons of differences in sample variance with differences in uncertainty estimates for measurements from different stars selected in a region of small natural variability.For GOMOS, the difference in sample variances for different stars at tangent altitudes 25-45 km is well explained by the difference in squared precisions, if the stars are not dim. Since this is observed for several stars, and since normalized χ 2 is close to 1 for these occultations in the stratosphere, we conclude that the GOMOS precision estimates are realistic in occultations of sufficiently bright stars. For dim stars, errors are overestimated due to improper accounting of the dark charge correction uncertainty in the error budget. The proposed method can also be applied to stratospheric ozone data from other instruments, including multi-instrument analyses.

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Section: F Sofieva Et Al: Validation Of Gomos Ozone Precision Esmentioning

confidence: 94%

Section: Specifics Of Gomos Measurements and Challenges For Precisionmentioning

confidence: 99%

Section: Outlines Of Gomos Precision Derivation and Characterization mentioning

confidence: 99%

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Validation of GOMOS ozone precision estimates in the stratosphere

et al. 2014

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“…An ongoing activity tries to map and estimate the effects from the (hopefully) minor processes so far neglected. The modelling errors from the omitted processes have been discussed in Tamminen et al (2010) of this special issue.…”

Section: Gomos Algorithm Developmentmentioning

confidence: 99%

Retrieval of atmospheric parameters from GOMOS data

et al. 2010

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Abstract. The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the European SpaceAgency's ENVISAT satellite measures attenuation of stellar light in occultation geometry. Daytime measurements also record scattered solar light from the atmosphere. The wavelength regions are the ultraviolet-visible band 248-690 nm and two infrared bands at 755-774 nm and at 926-954 nm. From UV-Visible and IR spectra the vertical profiles of O 3 , NO 2 , NO 3 , H 2 O, O 2 and aerosols can be retrieved. In addition there are two 1 kHz photometers at blue 473-527 nm and red 646-698 nm. Photometer data are used to correct spectrometer measurements for scintillations and to retrieve high resolution temperature profiles as well as gravity wave and turbulence parameters. Measurements cover altitude region 5-150 km. Atmospherically valid data are obtained in 15-100 km.In this paper we present an overview of the GOMOS retrieval algorithms for stellar occultation measurements. The low signal-to-noise ratio and the refractive effects due to the point source nature of stars have been important drivers in the development of GOMOS retrieval algorithms. We present first the Level 1b algorithms that are used to correct instrument related disturbances in the spectrometer and photometer measurements The Level 2 algorithms deal with the retrieval of vertical profiles of atmospheric gaseous constituents, aerosols and high resolution temperature. We divide the presentation into correction for refractive effects, Correspondence to: E. Kyrölä (erkki.kyrola@fmi.fi) high resolution temperature retrieval and spectral/vertical inversion. The paper also includes discussion about the GO-MOS algorithm development, expected improvements, access to GOMOS data and alternative retrieval approaches.

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“…The accuracy of the ozone profile derived from the GO-MOS retrieval depends on the star magnitude and temperature of the star Tamminen et al, 2010). The most accurate ozone profiles are retrieved using the hot and bright stars.…”

Section: Gomos Ozone Profilesmentioning

confidence: 99%