Technical note: Intermittent reduction of the stratospheric ozone over northern Europe caused by a storm in the Atlantic Ocean

• Published in: Atmospheric Chemistry and Physics
• Main Authors: M. Sofiev, R. Kouznetsov, R. Hänninen, V. F. Sofieva
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: Physics; QC1-999; Chemistry; QD1-999; Greenland; Siberia
• Online Access: https://doi.org/10.5194/acp-20-1839-2020; https://doaj.org/article/fcc0a0f72b164b0bb99f95f6ba7b1508

A 3 d episode of anomalously low ozone concentrations in the stratosphere over northern Europe occurred on 3–5 November 2018. A reduction of the total ozone column down to ∼ 200–210 Dobson units was predicted by the global forecasts of the System for Integrated modeLling of Atmospheric coMposition (SILAM) driven by the weather forecast of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The reduction down to 210–215 DU was subsequently observed by satellite instruments, such as the Ozone Monitoring Instrument (OMI) and Ozone Mapping Profile Suite (OMPS). The episode was caused by an intrusion of tropospheric air, which was initially uplifted by a storm in the northern Atlantic, south-east of Greenland. Subsequent transport towards the east and further uplift over the Scandinavian ridge of this humid and low-ozone air brought it to ∼25 km altitude, causing ∼30 % reduction of the ozone layer thickness over northern Europe. The low-ozone air was further transported eastwards and diluted over Siberia, so that the ozone concentrations were restored a few days later. Comparison of the model predictions with OMI, OMPS, and MLS (Microwave Limb Sounder) satellites demonstrated the high accuracy of the 5 d forecast of the IFS–SILAM system: the ozone anomaly was predicted within ∼10 DU accuracy and positioned within a couple of hundreds of kilometres. This episode showed the importance of the stratospheric composition dynamics and the possibility of its short-term forecasting, including such rare events.