Assessing the impact of clouds on ground-based UV–visible total column ozone measurements in the high Arctic

Xiaoyi Zhao (1, 2) , Kristof Bognar (1) , Vitali Fioletov (2) , Andrea Pazmino (3) , Florence Goutail (3) , Luis Millán (4) , Gloria Manney (5, 6) , Cristen Adams (7) , Kimberly Strong (1)

1 Department of Physics [Toronto]
2 ECCC - Environment and Climate Change Canada
3 STRATO - LATMOS
4 JPL - Jet Propulsion Laboratory
5 NWRA - NorthWest Research Associates
6 Department of Physics [Socorro]
7 EMSD - Environmental Monitoring and Science Division of Alberta

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 investigate 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, 8 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.

Domaines: Physique Atmosphérique et Océanique [physics.ao-ph]

Xiaoyi Zhao, Kristof Bognar, Vitali Fioletov, Andrea Pazmino, Florence Goutail, et al.. Assessing the impact of clouds on ground-based UV–visible total column ozone measurements in the high Arctic. Atmospheric Measurement Techniques, 2019, 12 (4), pp.2463-2483. ⟨10.5194/amt-12-2463-2019⟩. ⟨insu-02104733⟩