Identification of polar stratospheric clouds from the ground by visible spectrometry

Sarkissian, Alain; Pommereau, J. P.; Goutail, Florence

doi:10.1029/91gl00769

Cited by 50 publications

(45 citation statements)

References 11 publications

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“…The way to initialize this model is to specify the vertical profile of liquid water content and effective droplet radius. The microphysical properties of water clouds are then converted to optical properties according to the Hu and Stamnes (1993) (Sarkissian et al, 1991). Another source of uncertainty we have tested is the impact of surface albedo.…”

Section: Amf Lutsmentioning

confidence: 99%

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

et al. 2011

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Abstract. Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change) UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measuring total ozone twice daily with limited sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS spectral parameters and the calculation of air mass factors (AMF) needed for the conversion of O 3 slant column densities into vertical column amounts. The most important improvement is the use of O 3 AMF lookup tables calculated using the TOMS V8 (TV8) O 3 profile climatology, that allows accounting for the dependence of the O 3 AMF on the seasonal and latitudinal variations of the O 3 vertical distribution. To investigate their imCorrespondence to: F. Hendrick (franch@oma.be) pact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Système d'Analyse par Observation Zénithale) network. The revised SAOZ ozone data from eight stations deployed at all latitudes have been compared to TOMS, GOME-GDP4, SCIAMACHY-TOSOMI, SCIAMACHY-OL3, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments at Observatoire de Haute Provence (44 • N, 5.5 • E) and Sodankyla (67 • N, 27 • E), respectively. A significantly better agreement is obtained between SAOZ and correlative reference ground-based measurements after applying the new O 3 AMFs. However, systematic seasonal differences between SAOZ and satellite instruments remain. These are shown to mainly originate from (i) a possible problem in the satellite retrieval algorithms in dealing with the temperature dependence of the ozone cross-sections in the UV and the solar zenith angle (SZA) dependence, (ii) zonal modulations and seasonal variations of tropospheric ozone columns not accounted for in the TV8 profile climatology, and (iii) uncertainty on the stratospheric ozone profiles at high latitude in the winter in the TV8 climatology. For those measurements mostly sensitive to stratospheric temperature like TOMS, OMI-TOMS, Dobson and Brewer, or to SZA like Published by Copernicus Publications on behalf of the European Geosciences Union. 5976 F. Hendrick et al.: NDACC/SAOZ UV-visible total ozone measurements SCIAMACHY-TOSOMI, the application of temperature and SZA corrections results in the almost complete removal of the seasonal difference with SAOZ, improving significantly the consistency between all ground-based and satellite total ozone observations.

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Section: Amf Lutsmentioning

confidence: 99%

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

et al. 2011

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“…Sarkissian et al, 1991Sarkissian et al, , 1994Enell et al, 1999). In this study we calculate CI from measured detector signals at 320 nm and 440 nm:…”

Section: Colour Index (Ci)mentioning

confidence: 99%

Cloud detection and classification based on MAX-DOAS observations

et al. 2014

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Abstract. Multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations of aerosols and trace gases can be strongly influenced by clouds. Thus, it is important to identify clouds and characterise their properties. In this study we investigate the effects of clouds on several quantities which can be derived from MAX-DOAS observations, like radiance, the colour index (radiance ratio at two selected wavelengths), the absorption of the oxygen dimer O 4 and the fraction of inelastically scattered light (Ring effect). To identify clouds, these quantities can be either compared to their corresponding clear-sky reference values, or their dependencies on time or viewing direction can be analysed. From the investigation of the temporal variability the influence of clouds can be identified even for individual measurements. Based on our investigations we developed a cloud classification scheme, which can be applied in a flexible way to MAX-DOAS or zenith DOAS observations: in its simplest version, zenith observations of the colour index are used to identify the presence of clouds (or high aerosol load). In more sophisticated versions, other quantities and viewing directions are also considered, which allows subclassifications like, e.g., thin or thick clouds, or fog. We applied our cloud classification scheme to MAX-DOAS observations during the Cabauw intercomparison campaign of Nitrogen Dioxide measuring instruments (CINDI) campaign in the Netherlands in summer 2009 and found very good agreement with sky images taken from the ground and backscatter profiles from a lidar.

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“…As demonstrated by several intercomparison campaigns (Vaughan et al, 1997;Roscoe et al, 1999), the measurements of different SAOZ instruments are consistent within ±3% (about 15 DU). The presence of dense high altitude type II PSCs, which lead to an underestimation of total ozone in the zenith sky measurements because of the lifting of the scattering layer, is detected by a colour index method (Sarkissian et al, 1991). The corresponding ozone data are removed.…”

Section: Measurements and Modelsmentioning

confidence: 99%

Early unusual ozone loss during the Arctic winter 2002/2003 compared to other winters

Goutail¹,

Pommereau²,

Lefèvre³

et al. 2005

Atmos. Chem. Phys.

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Abstract. Ozone loss during the winter 2002/2003 has been evaluated from comparisons between total ozone reported by the SAOZ network and simulated in passive mode by both REPROBUS and SLIMCAT. Despite the fact that the two models have a different approach to calculate the descent inside vortex, both evaluations provide similar results 18±4% using REPROBUS and 20±4% using SLIMCAT and show that the loss started around mid-December, at least ten to twenty days earlier than during any of the previous eleven winters, except 1993/1994. This unusual behaviour is consistent with the low temperatures reported in the stratosphere as well to the signature of early chlorine activation indicated by ground-based, balloon and satellite observations. A significant ozone loss is also simulated by the current versions of two models, but of lesser amplitude compared to SAOZ, 13±2% for REPROBUS and 16±2% for SLIMCAT, the underestimation being already observed by mid-January. The early ozone depletion captured by both model show that chemical depletion did indeed take place in December, predominantly at the illuminated edge of the distorted vortex, but the reason for the underestimation compared to the observations and the differences among the models have still to be investigated.

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Identification of polar stratospheric clouds from the ground by visible spectrometry

Cited by 50 publications

References 11 publications

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

Cloud detection and classification based on MAX-DOAS observations

Early unusual ozone loss during the Arctic winter 2002/2003 compared to other winters

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