Occurrence of polar stratospheric clouds as derived from ground-based zenith DOAS observations using the colour index

• Published in: Atmospheric Chemistry and Physics
• Main Authors: B. Lauster, S. Dörner, C.-F. Enell, U. Frieß, M. Gu, J. Puķīte, U. Raffalski, T. Wagner
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2022
• Subjects: Physics; QC1-999; Chemistry; QD1-999; Neumayer; Kiruna; Antarc*; Antarctica
• Online Access: https://doi.org/10.5194/acp-22-15925-2022; https://doaj.org/article/4342c8bfc284469498fdae495ebf3413

Polar stratospheric clouds (PSCs) are an important component of ozone chemistry in polar regions. Studying the ozone-depleting processes requires a precise description of PSCs on a long-term basis. Although satellite observations already yield high spatial coverage, continuous ground-based measurements covering long time periods can be a valuable complement. In this study, differential optical absorption spectroscopy (DOAS) instruments are used to investigate the occurrence of PSCs based on the so-called colour index (CI), i.e. the colour of the zenith sky. Defined as the ratio between the observed intensities of scattered sunlight at two wavelengths, it provides a method to detect PSCs during twilight even in the presence of tropospheric clouds. We present data from instruments at the German research station Neumayer, Antarctica (71 ∘ S, 8 ∘ W), as well as Kiruna, Sweden (68 ∘ N, 20 ∘ E), which have been in operation for more than 20 years. For a comprehensive interpretation of the measurement data, the well-established radiative transfer model McArtim is used and radiances of scattered sunlight are simulated at several wavelengths for different solar zenith angles and various atmospheric conditions. The aim is to improve and evaluate the potential of this method. It is then used to infer the seasonal cycle and the variability of PSC occurrence throughout the time series measured in both hemispheres. A good agreement is found to satellite retrievals with deviations particularly in spring. The unexpectedly high signal observed in the DOAS data during springtime suggests the influence of volcanic aerosol. This is also indicated by enhanced aerosol extinction as seen from OMPS (Ozone Mapping and Profiler Suite) data but is not captured by other PSC climatologies. The presented approach allows the detection of PSCs for various atmospheric conditions not only for individual case studies but over entire time series, which is a decisive advance compared to previous work on the PSC detection by ground-based ...