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Winter Weather Regimes in the Northeast United States

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  • 1 Department of Environmental, Earth, and Atmospheric Sciences, University of Massachusetts Lowell, Lowell, Massachusetts
  • | 2 Department of Environmental, Earth, and Atmospheric Sciences, and Intercampus Marine Science Graduate Program, University of Massachusetts Lowell, Lowell, Massachusetts
  • | 3 Department of Environmental, Earth, and Atmospheric Sciences, and Climate Change Initiative, University of Massachusetts Lowell, Lowell, Massachusetts
  • | 4 Aix-Marseille University, CEREGE, UM 34 CNRS, Aix en Province, France
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Abstract

The method of k-means cluster analysis is applied to U.S. wintertime daily 850-hPa winds across the Northeast. The resulting weather patterns are analyzed in terms of duration, station, gridded precipitation, storm tracks, and climate teleconnections. Five distinct weather patterns are identified. Weather type (WT) 1 is characterized by a ridge over the western Atlantic and positive precipitation anomalies as far north as the Great Lakes; WT2, by a trough along the eastern United States and positive precipitation anomalies into southern New England; WT3, by a trough over the western Atlantic and negative precipitation anomalies along much of the U.S. East Coast; WT4, by a trough east of Newfoundland and negative precipitation anomalies along parts of the U.S. East Coast; and WT5, by a broad, shallow trough over southeastern Canada and negative precipitation anomalies over the entire U.S. East Coast. WT5 and WT1 are the most persistent, while WT2 typically progresses quickly to WT3 and then to WT4. Based on mean station precipitation in the northeastern United States, most precipitation occurs in WT2 and WT3, with the least in WT1 and WT4. Extreme precipitation occurs most frequently in WT2. Storm tracks show that WT2 and WT3 are associated with coastal storms, while WT2 is also associated with Great Lakes storms. Teleconnections are linked with a change in WT frequency by more than a factor of 2 in several cases: for the North Atlantic Oscillation (NAO) in WT1 and WT4 and for the Pacific–North American (PNA) pattern in WT1 and WT3.

Corresponding author address: Jian-Hua Qian, Department of Environmental, Earth, and Atmospheric Sciences, University of Massachusetts Lowell, One University Avenue, Lowell, MA 01854. E-mail: jianhua_qian@uml.edu

Abstract

The method of k-means cluster analysis is applied to U.S. wintertime daily 850-hPa winds across the Northeast. The resulting weather patterns are analyzed in terms of duration, station, gridded precipitation, storm tracks, and climate teleconnections. Five distinct weather patterns are identified. Weather type (WT) 1 is characterized by a ridge over the western Atlantic and positive precipitation anomalies as far north as the Great Lakes; WT2, by a trough along the eastern United States and positive precipitation anomalies into southern New England; WT3, by a trough over the western Atlantic and negative precipitation anomalies along much of the U.S. East Coast; WT4, by a trough east of Newfoundland and negative precipitation anomalies along parts of the U.S. East Coast; and WT5, by a broad, shallow trough over southeastern Canada and negative precipitation anomalies over the entire U.S. East Coast. WT5 and WT1 are the most persistent, while WT2 typically progresses quickly to WT3 and then to WT4. Based on mean station precipitation in the northeastern United States, most precipitation occurs in WT2 and WT3, with the least in WT1 and WT4. Extreme precipitation occurs most frequently in WT2. Storm tracks show that WT2 and WT3 are associated with coastal storms, while WT2 is also associated with Great Lakes storms. Teleconnections are linked with a change in WT frequency by more than a factor of 2 in several cases: for the North Atlantic Oscillation (NAO) in WT1 and WT4 and for the Pacific–North American (PNA) pattern in WT1 and WT3.

Corresponding author address: Jian-Hua Qian, Department of Environmental, Earth, and Atmospheric Sciences, University of Massachusetts Lowell, One University Avenue, Lowell, MA 01854. E-mail: jianhua_qian@uml.edu
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