{"title":"The Relationships between the Winter Circulation Regimes and the Northern Hemisphere 45-day Oscillation: A Combined Regime-Oscillation Framework","authors":"Mary H. Korendyke, David M. Straus","doi":"10.1175/mwr-d-23-0058.1","DOIUrl":null,"url":null,"abstract":"Abstract This paper analyzes the relationships between the circulation regimes of the 500 hPa height (z500) and 250 hPa zonal winds (u250) in the Pacific North America region during boreal winter, and the 45-day Northern Hemisphere oscillation identified by Stan and Krishnamurthy (2019) in z500. The regimes were calculated using a k-means clustering applied to the leading 12 Principal Components of the combined z500/u250 anomaly fields. We divided the oscillation into 8 arbitrary phases. The oscillation phase z500 composite maps are spatially well correlated with regime z500 composites: phases 1–2 are best correlated with the Arctic Low, phases 3–5 with the Pacific Trough, phase 6 with the Arctic High, and phases 7–8 with the Alaskan Ridge. We found that these correlations are generally consistent with the regimes that tend to occur during the individual oscillation phases: the Arctic Low occurs above significance in phases 1–2, the Pacific Trough in phase 3, and Alaskan Ridge in phases 7–8. Therefore, the oscillation has a preferred order with respect to the regimes. The regime transitions indicate a pattern that moves through the Pacific Wavetrain, a regime that appears for k=5 as a mean state. Transitions out of this regime into different regimes are preferred in different phases of the oscillation. These results imply a possible enhancement to regime prediction using the low-frequency oscillations in combination with regimes.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":"100 ","pages":"0"},"PeriodicalIF":2.8000,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Monthly Weather Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/mwr-d-23-0058.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract This paper analyzes the relationships between the circulation regimes of the 500 hPa height (z500) and 250 hPa zonal winds (u250) in the Pacific North America region during boreal winter, and the 45-day Northern Hemisphere oscillation identified by Stan and Krishnamurthy (2019) in z500. The regimes were calculated using a k-means clustering applied to the leading 12 Principal Components of the combined z500/u250 anomaly fields. We divided the oscillation into 8 arbitrary phases. The oscillation phase z500 composite maps are spatially well correlated with regime z500 composites: phases 1–2 are best correlated with the Arctic Low, phases 3–5 with the Pacific Trough, phase 6 with the Arctic High, and phases 7–8 with the Alaskan Ridge. We found that these correlations are generally consistent with the regimes that tend to occur during the individual oscillation phases: the Arctic Low occurs above significance in phases 1–2, the Pacific Trough in phase 3, and Alaskan Ridge in phases 7–8. Therefore, the oscillation has a preferred order with respect to the regimes. The regime transitions indicate a pattern that moves through the Pacific Wavetrain, a regime that appears for k=5 as a mean state. Transitions out of this regime into different regimes are preferred in different phases of the oscillation. These results imply a possible enhancement to regime prediction using the low-frequency oscillations in combination with regimes.
期刊介绍:
Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.