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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2018-261
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2018-261
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Sep 2018

Research article | 17 Sep 2018

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Atmospheric Measurement Techniques (AMT).

Assessing the Impact of Clouds on UV-visible Total Column Ozone Measurements in the High Arctic

Xiaoyi Zhao1,2, Kristof Bognar1, Vitali Fioletov2, Andrea Pazmino3, Florence Goutail3, Luis Millán4, Gloria Manney5,6, Cristen Adams7, and Kimberly Strong1 Xiaoyi Zhao et al.
  • 1Department of Physics, University of Toronto, Toronto, Ontario, M5S 1A7, Canada
  • 2Measurement and Analysis Research Section, Environment and Climate Change Canada, Toronto, M3H 5T4, Ontario, Canada
  • 3Versailles St-Quentin, CNRS/INSU, LATMOS-IPSL, 78280 Guyancourt, France
  • 4Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
  • 5NorthWest Research Associates, Socorro, New Mexico, USA
  • 6Department of Physics, New Mexico Institute of Mining and Technology, Socorro, New Mexico , USA
  • 7Environmental Monitoring and Science Division, Government of Alberta, Edmonton, Alberta, Canada

Abstract. Zenith-Sky scattered light Differential Optical Absorption Spectroscopy (ZS-DOAS) has been used widely to retrieve total column ozone (TCO). ZS-DOAS measurements have the advantage of being less sensitive to clouds than direct-sun measurements. However, the presence of clouds still affects the quality of ZS-DOAS TCO. Clouds are thought to be the largest contributor to random uncertainty in ZS-DOAS TCO, but their impact on data quality still needs to be quantified. This study has two goals: (1) to study whether clouds have a significant impact on ZS-DOAS TCO, and (2) to develop a cloud-screening algorithm to improve ZS-DOAS measurements in the Arctic under cloudy conditions. To quantify the impact of weather, eight years of measured and modelled TCO have been used, along with information about weather conditions at Eureka, Canada (80.05° N, 86.41° W). Relative to direct-sun TCO measurements by Brewer spectrophotometers and modelled TCO, a positive bias is found in ZS-DOAS TCO measured in cloudy weather, and a negative bias is found for clear conditions, with differences of up to 5 % between clear and cloudy conditions. A cloud-screening algorithm is developed for high-latitudes using the colour index calculated from ZS-DOAS spectra. The quality of ZS-DOAS TCO datasets is assessed using a statistical uncertainty estimation model, which suggests a 3–4 % random uncertainty. The new cloud-screening algorithm reduces the random uncertainty by 0.6 %. If all measurements collected during cloudy conditions, as identified using the weather station observations, are removed, the random uncertainty is reduced by 1.3 %. This work demonstrates that clouds are a significant contributor to uncertainty in ZS-DOAS TCO and proposes a method that can be used to screen clouds in high-latitude spectra.

Xiaoyi Zhao et al.
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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Xiaoyi Zhao et al.
Xiaoyi Zhao et al.
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