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. Zenith-Sky scattered lightDifferential Optical Absorption Spectroscopy (ZS-DOAS) has been used widelyto retrieve total column ozone (TCO). ZS-DOAS measurements have the advantageof being less sensitive to clouds than direct-sun measurements. However, thepresence of clouds still affects the quality of ZS-DOAS TCO. Clouds arethought 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 hastwo goals: (1) to investigate whether clouds have a significant impact onZS-DOAS TCO, and (2) to develop a cloud-screening algorithm to improveZS-DOAS measurements in the Arctic under cloudy conditions. To quantify theimpact of weather, 8 years of measured and modelled TCO have been used, alongwith information about weather conditions at Eureka, Canada(80.05 ∘  N, 86.41 ∘  W). Relative to direct-sun TCOmeasurements by Brewer spectrophotometers and modelled TCO, a positive biasis found in ZS-DOAS TCO measured in cloudy weather, and a negative bias isfound for clear conditions, with differences of up to 5 % between clearand cloudy conditions. A cloud-screening algorithm is developed for highlatitudes using the colour index calculated from ZS-DOAS spectra. The qualityof ZS-DOAS TCO datasets is assessed using a statistical uncertaintyestimation model, which suggests a 3 %–4 % random uncertainty. Thenew cloud-screening algorithm reduces the random uncertainty by 0.6 %. Ifall measurements collected during cloudy conditions, as identified using theweather station observations, are removed, the random uncertainty is reducedby 1.3 %. This work demonstrates that clouds are a significantcontributor to uncertainty in ZS-DOAS TCO and proposes a method that can beused to screen clouds in high-latitude spectra.

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