Prediction of Northern Hemisphere regional sea ice extent and snow depth using stratospheric ozone information

The forecast potential of springtime ozone on April surface temperatures at particular locations in the Northern Hemisphere has been previously reported. Evidence suggests that early springtime Arctic stratospheric ozone acts as a proxy for extreme events in the winter polar vortex. Here, using a state-of-the-art chemistry-climate model, reanalysis and observations, we extend the forecast potential of ozone on surface temperatures to aspects of the Northern Hemisphere cryosphere. Sea ice fraction and sea ice extent differences between years of March high and low Arctic stratospheric ozone extremes show excellent agreement between an ensemble of chemistry-climate model simulations and observations, with differences occurring not just in April but extending through to the following winter season in some locations. Large snow depth differences are also obtained in regional locations in Russia and along the southeast coast of Alaska. These differences remain elevated until early summer, when snow cover diminishes. Using a conditional empirical model in a leave-three-out cross validation method, March total column ozone is able to accurately predict the sign of the observed sea ice extent and snow depth anomalies over 70% of the time during an ozone extreme year, especially in the region of the Bering strait and the Greenland Sea, which could be useful for shipping routes and for testing climate models.

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Copyright 2020 American Geophysical Union.


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Author Stone, K. A.
Solomon, S.
Kinnison, Douglas E.
Publisher UCAR/NCAR - Library
Publication Date 2020-11-27T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2025-07-11T19:13:00.360595
Metadata Record Identifier edu.ucar.opensky::articles:23860
Metadata Language eng; USA
Suggested Citation Stone, K. A., Solomon, S., Kinnison, Douglas E.. (2020). Prediction of Northern Hemisphere regional sea ice extent and snow depth using stratospheric ozone information. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7gm8bnc. Accessed 02 August 2025.

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