Ocean Temperature Observations in Hurricane Dorian (2019)

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Monthly Weather Review Pub Date : 2023-05-10 DOI:10.1175/mwr-d-22-0271.1
Casey R. Densmore, E. Sanabia, S. Jayne
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引用次数: 1

Abstract

Upper ocean temperatures from 72 Airborne eXpendable BathyThermographs (AXBTs) collected during Air Force Hurricane Hunter flights into Hurricane Dorian (2019) over a 72-hour period are examined. Three transects collected behind the storm reveal increased cross-track sea surface temperature gradient magnitudes as Dorian intensified to a category-5 hurricane and slowed while approaching the Bahamas. The cold wake, evident in vertical and horizontal cross sections from in-situ and satellite sensors, appears as an expected response to tropical cyclone passage. Atypical, however, is the 2°C surface cooling observed over 36 hours in a pair of transects ahead of hurricane force winds in Dorian, likely due to changes in the tropical cyclone’s translation speed and direction and/or proximity to the Gulf Stream and continental shelf. Co-located AXBT pairs document a dynamical regime shift from mixing to upwelling as Dorian slows and turns. Relationships between time-integrated wind stress and sea surface temperature indicate track-relative differences varying with storm translation speed and heading changes, paralleling the shift in cooling dynamics.
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飓风多里安的海洋温度观测(2019)
研究了在空军飓风猎人飞往飓风多里安(2019)72小时内收集的72个机载消耗性深海温度仪(axts)的上层海洋温度。在风暴背后收集的三个横断面显示,随着多里安增强为5级飓风,并在接近巴哈马群岛时减速,交叉海道的海面温度梯度增加。从原位和卫星传感器的垂直和水平横截面来看,冷尾流是对热带气旋通过的预期响应。然而,非典型的是,在多里安飓风之前的36小时内,在一对横断面上观测到的2°C的地表冷却,可能是由于热带气旋的移动速度和方向的变化,以及/或靠近墨西哥湾流和大陆架。当多里安变慢并转向时,位于同一位置的AXBT对记录了从混合到上升流的动力转变。时间积分风应力和海面温度之间的关系表明,路径相对差异随风暴平移速度和风向变化而变化,与冷却动力学的变化平行。
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来源期刊
Monthly Weather Review
Monthly Weather Review 地学-气象与大气科学
CiteScore
6.40
自引率
12.50%
发文量
186
审稿时长
3-6 weeks
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.
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