Polar Lows

doi:10.1017/cbo9780511524974

Cited by 207 publications

(14 citation statements)

References 345 publications

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“…It should be noted that more than half of the cyclone identification methods presented in the Intercomparison of Mid Latitude Storm Diagnostics project (Neu et al, 2013) are pressure-based identification methods. MSLP fields are also used to detect intense polar mesocyclones (polar lows) in the Arctic that form during the cold season over the relatively warm open water in the Arctic (Rasmussen & Turner, 2003). Cyclones can also be detected based on vorticity maps.…”

Section: Cyclone Identificationmentioning

confidence: 99%

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

et al. 2018

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The ability of state‐of‐the‐art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic‐CORDEX initiative. Some models employ large‐scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA‐Interim, National Centers for Environmental Prediction‐Climate Forecast System Reanalysis, National Aeronautics and Space Administration‐Modern‐Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency‐Japanese 55‐year reanalysis) in winter and summer for 1981–2010 period. In addition, we compare cyclone statistics between ERA‐Interim and the Arctic System Reanalysis reanalyses for 2000–2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large‐scale spectral nudging show a better agreement with ERA‐Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

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Section: Cyclone Identificationmentioning

confidence: 99%

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

et al. 2018

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“…While several atmospheric phenomena can be at the origin of strong surface winds, inward spiraling winds generated by synoptic-scale cyclones are so powerful and cyclones of different types and categories are considered to be the most powerful atmospheric features around the globe (e.g., Orlanski, 1975;Rudeva & Gulev, 2007) given their significant impacts on the environment on a synoptic scale as a result of the extremely high energy they carry (e.g., Bou Karam et al, 2010;Francis et al, 2018). This is particularly true in polar areas, where polar cyclones are intense and their impact on the surface is believed to be considerable (Kolstad, 2011;Rasmussen & Turner, 2003;Simmonds et al, 2008). In the Southern Hemisphere, where cyclonic winds spin clockwise, the highest wind speed occurs along the bent-back front of the cyclone, that is, to the left of the low-pressure center of the cyclone (Wagner et al, 2011;Watanabe & Niino, 2014).…”

Section: Introductionmentioning

confidence: 99%

Polar Cyclones at the Origin of the Reoccurrence of the Maud Rise Polynya in Austral Winter 2017

et al. 2019

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This study examines the role of atmospheric forcings in the occurrence of open‐ocean polynyas by investigating the case of the austral winter 2017's polynya located in the Lazarev Sea sector to the east of the Weddell Sea, known as the Maud Rise polynya or the Weddell Polynya. The ice‐free zone appeared in mid‐September 2017 and grew to as large as 80,000 km2 by the end of October 2017 before merging with the open ocean after the sea ice started to retreat at the beginning of the austral summer. Using a combination of satellite observations and reanalysis data at high spatiotemporal resolution, we found that severe cyclones, occurring over the ice pack, have a deterministic role in creating strong divergence in the sea ice field through strong cyclonic surface winds leading to the opening of the polynya. The occurrence of intense and frequent cyclones over the ice pack during austral winter 2017 was unusual, and it occurred under an enhanced strong positive meridional transport of heat flux and moisture toward Antarctica associated with an amplification of the atmospheric zonal wave 3 and a strong positive Southern Annular Mode index. We found that the opening of the polynya was not primarily due to direct ice melt by thermodynamic effects but rather to strong dynamical forcing by the winds on the sea ice, as in the case of coastal polynyas. Indeed, the meridional transport of heat toward Antarctica occurred over the Weddell Sea sector (i.e., to the east of the Lazarev Sea sector where the polynya is located) whereas the Lazarev Sea sector was under the influence of equatorward transport of cold air masses at that time. Our results show that the supply of warm and moist air coming from the west side of the South Atlantic Ocean into the Weddell Sea significantly increased the potential for cyclone formation as measured by the Eady growth rate leading to intense and frequent cyclogenesis over the ice pack, far south from the ice edge. After cyclogenesis in the Weddell Sea, these cyclones intensified as they moved eastward spinning over the Lazarev Sea with intensity comparable to category 11—violent storms—in the Beaufort scale. The cyclonic winds generated sea ice divergence by pushing the ice away from the cyclone center: To the east, north of it and to the west, south of it, which led to the reoccurrence of the Maud Rise polynya in mid‐September 2017.

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“…море с учетом ледовых условий В северо-западной части Гренландского моря 30.12.1974 г. вдоль кромки льда, где в своем большинстве ПЦ обычно и зарождаются [2,37], началось формирование исследуемого циклона. Адвекция холодного воздуха с покрытой льдом поверхности на свободную от льда водную поверхность привела к развитию сильной вертикальной неустойчивости и конвекции, которые и являются основными причинами зарождения интенсивных ПЦ [1,2].…”

Section: воспроизведение параметров полярного циклона 1975 г в баренunclassified

“…Введение Изучение морей высоких широт не представляется возможным без использования современных методов численного моделирования вследствие труднодоступности и суровых климатических условий Арктического бассейна. Это особенно актуально для изучения отклика верхнего слоя моря на прохождение интенсивных полярных циклонов (ПЦ), которые регулярно наблюдаются в акватории Баренцева моря [1,2]. Горизонтальный масштаб ПЦ составляет приблизительно 150-600 км, а устойчивый ветер на высоте 10 м превышает 13,8 м/с -силу шторма более 7 баллов по шкале Бофорта [2].…”

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“…Это особенно актуально для изучения отклика верхнего слоя моря на прохождение интенсивных полярных циклонов (ПЦ), которые регулярно наблюдаются в акватории Баренцева моря [1,2]. Горизонтальный масштаб ПЦ составляет приблизительно 150-600 км, а устойчивый ветер на высоте 10 м превышает 13,8 м/с -силу шторма более 7 баллов по шкале Бофорта [2]. Максимальные скорости ветра в ПЦ часто превышают 22 м/с.…”

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Investigation of the Barents Sea Upper Layer Response to the Polar Low in 1975

Diansky¹,

Panasenkova²,

Фомін³

2019

MGZh

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The present paper is focused on reproducing the extreme polar low observed over the Barents Sea in early January 1975, on the metocean hindcast data and on analyzing the upper sea layer response to the cyclone passage. Methods and Results. All the calculations are carried out based on the Marine and Atmospheric Research System for simulating hydrometeorological characteristics of the western seas in the Russian Arctic (the Barents, White, Pechora and Kara seas). The main components of this system are the regional non-hydrostatic model of atmospheric circulation WRF (spatial resolution is 15 km) and the physically complete three-dimensional σ-model of marine circulation INMOM (spatial resolution is 2.7 km). The atmospheric reanalysis data and the results of previous studies are used. The polar low produced a severe impact on the central and eastern parts of the Barents Sea, namely, being strongly influenced by the storm winds, the near-surface current velocities changed significantly. During a storm period in these parts of the Barents Sea, the drift component prevails over the tidal one. The tidal component prevails in the shallow southern part of the Barents Sea even during the most extreme storm period. It is shown that a polar low can lead to increase of the sea surface temperature in the Barents Sea by more than 1°С. Conclusion. The sea surface temperature positive anomaly is formed by the dynamic processes associated with vertical mixing, upwelling in the western and central parts of the Barents Sea, the Ekman drift and downwelling near the Novaya Zemlya coast. Contribution of the sea-atmosphere heat exchange to formation of the surface temperature positive anomalies is negligible. On the contrary, in the southern part of the Barents Sea and in the Pechora Sea, a significant surface temperature decrease (by almost 1.5°С) is observed during a polar low passing. This is a result of the sea upper layer cooling due to the heat transfer from the sea surface to the atmosphere.

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Polar Lows

Cited by 207 publications

References 345 publications

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

Polar Cyclones at the Origin of the Reoccurrence of the Maud Rise Polynya in Austral Winter 2017

Investigation of the Barents Sea Upper Layer Response to the Polar Low in 1975

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