Case study of ozone anomalies over northern Russia in the 2015/2016 winter: measurements and numerical modelling

Timofeyev, Yury; Smyshlyaev, S. P.; Virolainen, Ya. A.; Garkusha, A. S.; Polyakov, A. V.; Motsakov, M. A.; Kirner, Oliver

doi:10.5194/angeo-36-1495-2018

Cited by 14 publications

(2 citation statements)

References 27 publications

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“…Nevertheless, in January-February 2016, lower values of the total column ozone (up to ~200 Dobson Units (DU)) were observed in the northern part of Russia, which was 50% less than the average climatic values [20]. Analysis of the model simulation revealed that these anomalies were mainly due to Dynamic reasons [21].…”

Section: Introductionmentioning

confidence: 94%

Numerical Modeling of Ozone Loss in the Exceptional Arctic Stratosphere Winter–Spring of 2020

2021

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Dynamical processes and changes in the ozone layer in the Arctic stratosphere during the winter of 2019–2020 were analyzed using numerical experiments with a chemistry-transport model (CTM) and reanalysis data. The results of numerical calculations using CTM with Dynamic parameters specified from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis data, carried out according to several scenarios of accounting for the chemical destruction of ozone, demonstrated that both Dynamic and chemical processes contribute significantly to ozone changes over the selected World Ozone and Ultraviolet Radiation Data Centre network stations, both in the Eastern and in the Western hemispheres. Based on numerical experiments with the CTM, the specific Dynamic conditions of winter–spring 2019–2020 described a decrease in ozone up to 100 Dobson Units (DU) in the Eastern Hemisphere and over 150 DU in the Western Hemisphere. In this case, the photochemical destruction of ozone in both the Western and Eastern Hemispheres at a maximum was about 50 DU with peaks in April in the Eastern Hemisphere and in March and April in the Western Hemisphere. Heterogeneous activation of halogen gases on the surface of polar stratospheric clouds, on the one hand, led to a sharp increase in the destruction of ozone in chlorine and bromine catalytic cycles, and, on the other hand, decreased its destruction in nitrogen catalytic cycles. Analysis of wave activity using 3D Plumb fluxes showed that the enhancement of upward wave activity propagation in the middle of March over the Gulf of Alaska was observed during the development stage of the minor sudden stratospheric warming (SSW) event that led to displacement of the stratospheric polar vortex to the north of Canada and decrease of polar stratospheric clouds’ volume.

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Section: Introductionmentioning

confidence: 94%

Numerical Modeling of Ozone Loss in the Exceptional Arctic Stratosphere Winter–Spring of 2020

2021

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“…Nowadays, there are many chemistry-transport models (CTMs) and chemistry-climate models (CCMs) which differ in coverage of the Earth (global and regional), spatial and temporal resolution, considered physical and chemical processes and other characteristics. Series of studies have demonstrated successful implementation of the models for investigating the atmospheric ozone content variations, determination of main factors influencing stratospheric ozone and estimation of the future and past of the ozonosphere [36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Measurements and Modelling of Total Ozone Columns near St. Petersburg, Russia

et al. 2022

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The observed ozone layer depletion is influenced by continuous anthropogenic activity. This fact enforced the regular ozone monitoring globally. Information on spatial-temporal variations in total ozone columns (TOCs) derived by various observational methods and models can differ significantly due to measurement and modelling errors, differences in ozone retrieval algorithms, etc. Therefore, TOC data derived by different means should be validated regularly. In the current study, we compare TOC variations observed by ground-based (Bruker IFS 125 HR, Dobson, and M-124) and satellite (OMI, TROPOMI, and IKFS-2) instruments and simulated by models (ERA5 and EAC4 re-analysis, EMAC and INM RAS—RSHU models) near St. Petersburg (Russia) between 2009 and 2020. We demonstrate that TOC variations near St. Petersburg measured by different methods are in good agreement (with correlation coefficients of 0.95–0.99). Mean differences (MDs) and standard deviations of differences (SDDs) with respect to Dobson measurements constitute 0.0–3.9% and 2.3–3.7%, respectively, which is close to the actual requirements of the quality of TOC measurements. The largest bias is observed for Bruker 125 HR (3.9%) and IKFS-2 (−2.4%) measurements, whereas M-124 filter ozonometer shows no bias. The largest SDDs are observed for satellite measurements (3.3–3.7%), the smallest—for ground-based data (2.3–2.8%). The differences between simulated and Dobson data vary significantly. ERA5 and EAC4 re-analysis data show slight negative bias (0.1–0.2%) with SDDs of 3.7–3.9%. EMAC model overestimates Dobson TOCs by 4.5% with 4.5% SDDs, whereas INM RAS-RSHU model underestimates Dobson by 1.4% with 8.6% SDDs. All datasets demonstrate the pronounced TOC seasonal cycle with the maximum in spring and minimum in autumn. Finally, for 2004–2021 period, we derived a significant positive TOC trend near St. Petersburg (~0.4 ± 0.1 DU per year) from all datasets considered.

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