Revealing Weekly-Scale Drivers of North American Winter Storm Track Variability Using a Causal Discovery Framework.
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| Title: | Revealing Weekly-Scale Drivers of North American Winter Storm Track Variability Using a Causal Discovery Framework. |
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| Authors: | SHAN HE1 heshan9@alumni.sysu.edu.cn, CHANG, EDMUND K. M.1, CHENG ZHENG1, JAEYEON LEE2, XIAOSONG YANG3 |
| Source: | Journal of Climate. Jun2026, Vol. 39 Issue 11, p1-15. 15p. |
| Subjects: | Causal models, Atmospheric circulation, Rossby waves, North Atlantic oscillation, Weather forecasting, Ocean temperature, Vertical wind shear |
| Geographic Terms: | North America, United States, Pacific Coast (U.S.), North Pacific Ocean, Atlantic Ocean |
| Abstract: | Storm tracks frequently produce winter weather extremes across North America. However, their weekly-scale variability remains challenging to explain, since atmospheric and oceanic processes, both local and remote, interact in complex ways. This study uses a causal discovery framework to pinpoint and evaluate the drivers of the North American winter storm track activity on a weekly scale. Unlike correlation-based statistical methods, causal discovery methods factor in confounders and time dependence, enabling them to distinguish true drivers from spurious associations. By incorporating a resampling procedure, the framework quantifies the degree of confidence for candidate drivers, thus revealing the most probable pathways influencing the storm track variability. The two strongest pathways are analyzed. The first arises from anomalous atmospheric circulation over the North Pacific. This anomaly excites a quasi-stationary Rossby wave train to affect the vertical wind shear over the U.S. West Coast one week later. Hence, the downstream baroclinic development changes, thereby altering the storm track activity over central–eastern North America. The second pathway involves rapid air–sea coupling over the North Atlantic, where the low-level wind anomalies related to the North Atlantic Oscillation alter surface heat fluxes to induce a tripolar pattern of sea surface temperature (SST) anomalies one week later. This SST tripole then affects the baroclinicity upstream and thus the storm track activity over northern North America. By isolating different processes that drive storm track variability, the framework could enhance our understanding and prediction of midlatitude weather as well as climate. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Storm tracks frequently produce winter weather extremes across North America. However, their weekly-scale variability remains challenging to explain, since atmospheric and oceanic processes, both local and remote, interact in complex ways. This study uses a causal discovery framework to pinpoint and evaluate the drivers of the North American winter storm track activity on a weekly scale. Unlike correlation-based statistical methods, causal discovery methods factor in confounders and time dependence, enabling them to distinguish true drivers from spurious associations. By incorporating a resampling procedure, the framework quantifies the degree of confidence for candidate drivers, thus revealing the most probable pathways influencing the storm track variability. The two strongest pathways are analyzed. The first arises from anomalous atmospheric circulation over the North Pacific. This anomaly excites a quasi-stationary Rossby wave train to affect the vertical wind shear over the U.S. West Coast one week later. Hence, the downstream baroclinic development changes, thereby altering the storm track activity over central–eastern North America. The second pathway involves rapid air–sea coupling over the North Atlantic, where the low-level wind anomalies related to the North Atlantic Oscillation alter surface heat fluxes to induce a tripolar pattern of sea surface temperature (SST) anomalies one week later. This SST tripole then affects the baroclinicity upstream and thus the storm track activity over northern North America. By isolating different processes that drive storm track variability, the framework could enhance our understanding and prediction of midlatitude weather as well as climate. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 08948755 |
| DOI: | 10.1175/JCLI-D-25-0497.1 |
