Elliptical Orbit Representation for the Annual Evolution of the Northern Hemisphere Stratospheric Polar Vortex. Part II: Long‐Lead Forecasts of Wintertime S2S Anomalies.
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| Title: | Elliptical Orbit Representation for the Annual Evolution of the Northern Hemisphere Stratospheric Polar Vortex. Part II: Long‐Lead Forecasts of Wintertime S2S Anomalies. |
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| Authors: | Secor, Michael1 (AUTHOR), Sun, Jie1 (AUTHOR), Yu, Yueyue2 (AUTHOR), Wu, Zhaohua1 (AUTHOR), Cai, Ming1 (AUTHOR) mcai@fsu.edu |
| Source: | Journal of Geophysical Research. Atmospheres. 3/16/2026, Vol. 131 Issue 5, p1-23. 23p. |
| Subject Terms: | *Long-range weather forecasting, *Atmospheric circulation, Stratospheric circulation, Ellipses (Geometry), Statistical models |
| Geographic Terms: | Northern Hemisphere |
| Abstract: | In Part I, we represent the annual evolution of the Northern Hemisphere stratospheric polar vortex (SPV) in individual years using an ellipse, defined through six ellipse parameters, for the phase‐space trajectory of the daily time series of MU (mass‐weighted zonally integrated zonal wind at 60°N above 400 K) and M (stratospheric air mass over 60–90°N above 400 K) from July 1 to June 30 of the following year. Building on that foundation, this study puts forward a new paradigm for long‐lead forecasts of wintertime SPV anomalies through predicting the six ellipse parameters before the cold season. A set of 17 predictors for predicting these yearly‐varying ellipse parameters, computed exclusively from data available before October 1, are selected from three primary sources: external factors, isentropic mass circulation indices, and phase‐space trajectory precursors. The regression models exhibit high predictive skill with cross‐year correlations between predicted and observed ellipse parameters ranging from 0.79 to 0.91. When translated through the elliptical representation, yearly predicted ellipse parameters yield skillful forecasts of continuously evolving subseasonal‐to‐seasonal (S2S) anomalies of the SPV from October through the following April. The correlation skill of forecasts for seasonal‐mean SPV anomalies remains above 0.8 at lead times of one to 6 months, and that for two‐weekly anomalies is still above 0.6 over lead times of two to 5 months. The forecasts also capture the amplitude and timing of wintertime SPV extrema. These results demonstrate that the elliptical representation provides a skillful framework for long‐lead forecasting of SPV anomalies at S2S scales. Plain Language Summary: This study develops a new way to predict how the Northern Hemisphere stratospheric polar vortex (SPV) evolves over the course of a year. Building on a method from Part I that describes the SPV's annual changes using a simple elliptical orbit trajectory, we use statistical models to forecast the six ellipse parameters on a yearly basis. The statistical models rely on 17 predictors, including external factors like ozone levels and snow cover, and the strength of diabatic and adiabatic isentropic mass fluxes. These predictors are available before October 1 each year, allowing for early forecasts for these yearly‐varying ellipse parameters. The predicted ellipse parameters are then used to reconstruct the temporal evolution of the SPV throughout fall, winter, and spring. The results show high accuracy, especially during winter when the SPV varies most. This framework allows for skillful long‐lead forecasts of subseasonal‐to‐seasonal SPV anomalies at lead times beyond 1 month, offering a practical tool for improving extended weather and climate predictions. Key Points: A new method predicts the yearly evolution of the Northern Hemisphere stratospheric polar vortex (SPV) using six ellipse parametersThe forecasts accurately capture subseasonal‐to‐seasonal SPV anomalies at lead times beyond 1 monthThe forecasts outperform both dynamical and statistical S2S forecasts [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Geophysical Research. Atmospheres is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 192266624 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Elliptical Orbit Representation for the Annual Evolution of the Northern Hemisphere Stratospheric Polar Vortex. Part II: Long‐Lead Forecasts of Wintertime S2S Anomalies. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Secor%2C+Michael%22">Secor, Michael</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Jie%22">Sun, Jie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yu%2C+Yueyue%22">Yu, Yueyue</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Zhaohua%22">Wu, Zhaohua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cai%2C+Ming%22">Cai, Ming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mcai@fsu.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Geophysical+Research%2E+Atmospheres%22">Journal of Geophysical Research. Atmospheres</searchLink>. 3/16/2026, Vol. 131 Issue 5, p1-23. 23p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Long-range+weather+forecasting%22">Long-range weather forecasting</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmospheric+circulation%22">Atmospheric circulation</searchLink><br /><searchLink fieldCode="DE" term="%22Stratospheric+circulation%22">Stratospheric circulation</searchLink><br /><searchLink fieldCode="DE" term="%22Ellipses+%28Geometry%29%22">Ellipses (Geometry)</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Northern+Hemisphere%22">Northern Hemisphere</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In Part I, we represent the annual evolution of the Northern Hemisphere stratospheric polar vortex (SPV) in individual years using an ellipse, defined through six ellipse parameters, for the phase‐space trajectory of the daily time series of MU (mass‐weighted zonally integrated zonal wind at 60°N above 400 K) and M (stratospheric air mass over 60–90°N above 400 K) from July 1 to June 30 of the following year. Building on that foundation, this study puts forward a new paradigm for long‐lead forecasts of wintertime SPV anomalies through predicting the six ellipse parameters before the cold season. A set of 17 predictors for predicting these yearly‐varying ellipse parameters, computed exclusively from data available before October 1, are selected from three primary sources: external factors, isentropic mass circulation indices, and phase‐space trajectory precursors. The regression models exhibit high predictive skill with cross‐year correlations between predicted and observed ellipse parameters ranging from 0.79 to 0.91. When translated through the elliptical representation, yearly predicted ellipse parameters yield skillful forecasts of continuously evolving subseasonal‐to‐seasonal (S2S) anomalies of the SPV from October through the following April. The correlation skill of forecasts for seasonal‐mean SPV anomalies remains above 0.8 at lead times of one to 6 months, and that for two‐weekly anomalies is still above 0.6 over lead times of two to 5 months. The forecasts also capture the amplitude and timing of wintertime SPV extrema. These results demonstrate that the elliptical representation provides a skillful framework for long‐lead forecasting of SPV anomalies at S2S scales. Plain Language Summary: This study develops a new way to predict how the Northern Hemisphere stratospheric polar vortex (SPV) evolves over the course of a year. Building on a method from Part I that describes the SPV's annual changes using a simple elliptical orbit trajectory, we use statistical models to forecast the six ellipse parameters on a yearly basis. The statistical models rely on 17 predictors, including external factors like ozone levels and snow cover, and the strength of diabatic and adiabatic isentropic mass fluxes. These predictors are available before October 1 each year, allowing for early forecasts for these yearly‐varying ellipse parameters. The predicted ellipse parameters are then used to reconstruct the temporal evolution of the SPV throughout fall, winter, and spring. The results show high accuracy, especially during winter when the SPV varies most. This framework allows for skillful long‐lead forecasts of subseasonal‐to‐seasonal SPV anomalies at lead times beyond 1 month, offering a practical tool for improving extended weather and climate predictions. Key Points: A new method predicts the yearly evolution of the Northern Hemisphere stratospheric polar vortex (SPV) using six ellipse parametersThe forecasts accurately capture subseasonal‐to‐seasonal SPV anomalies at lead times beyond 1 monthThe forecasts outperform both dynamical and statistical S2S forecasts [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Geophysical Research. Atmospheres is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1029/2025JD044222 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 1 Subjects: – SubjectFull: Long-range weather forecasting Type: general – SubjectFull: Atmospheric circulation Type: general – SubjectFull: Stratospheric circulation Type: general – SubjectFull: Ellipses (Geometry) Type: general – SubjectFull: Statistical models Type: general – SubjectFull: Northern Hemisphere Type: general Titles: – TitleFull: Elliptical Orbit Representation for the Annual Evolution of the Northern Hemisphere Stratospheric Polar Vortex. Part II: Long‐Lead Forecasts of Wintertime S2S Anomalies. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Secor, Michael – PersonEntity: Name: NameFull: Sun, Jie – PersonEntity: Name: NameFull: Yu, Yueyue – PersonEntity: Name: NameFull: Wu, Zhaohua – PersonEntity: Name: NameFull: Cai, Ming IsPartOfRelationships: – BibEntity: Dates: – D: 16 M: 03 Text: 3/16/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 2169897X Numbering: – Type: volume Value: 131 – Type: issue Value: 5 Titles: – TitleFull: Journal of Geophysical Research. Atmospheres Type: main |
| ResultId | 1 |
