Diagnosing flavors of tropospheric Rossby wave breaking and their associated dynamical and sensible weather features

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Grant LaChat, K. Bowley, Melissa Gervais
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引用次数: 0

Abstract

Rossby wave breaking (RWB) can be manifested by the irreversible overturning of isentropes on constant potential vorticity (PV) surfaces. Traditionally, the type of breaking is categorized as anticyclonic (AWB) or cyclonic (CWB) and can be identified using the orientation of streamers of high potential temperature (θ) and low θ air on a PV surface. However, an examination of the differences in RWB structure and their associated tropospheric impacts within these types remains unexplored. In this study, AWB and CWB are identified from overturning isentropes on the dynamic tropopause (DT), defined as the 2 potential vorticity unit (PVU) surface, in the ERA5 reanalysis dataset during December, January, and February 1979–2019. Self-organizing maps (SOM), a machine learning method, is used to cluster the identified RWB events into archetypal patterns, or “flavors”, for each type. AWB and CWB flavors capture variations in the θ minima/maxima of each streamer and the localized meridional θ gradient (∇θ) flanking the streamers. Variations in the magnitude and position of ∇θ between flavors correspond to a diversity of jet structures leading to differences in vertical motion patterns and troposphere-deep circulations. A subset of flavors of AWB (CWB) events are associated with the development of strong surface high (low) pressure systems and the generation of extreme poleward moisture transport. For CWB, many events occurred in similar geographical regions, but the precipitation and moisture patterns were vastly different between flavors. Our findings suggest that the location, type, and severity of the tropospheric impacts from RWB are strongly dictated by RWB flavor.
诊断对流层罗斯比波破碎的味道及其相关的动力学和可感天气特征
罗斯比破波(RWB)表现为恒定位涡(PV)表面上等涡线的不可逆翻转。传统上,断裂类型分为反气旋型(AWB)和气旋型(CWB),可通过 PV 表面上高势温(θ)和低θ空气流线的方向来识别。然而,对这些类型中 RWB 结构的差异及其相关的对流层影响的研究仍未进行。在这项研究中,从 1979 年至 2019 年 12 月、1 月和 2 月期间ERA5 再分析数据集中的动态对流层顶(DT)(定义为 2 个潜在涡度单位(PVU)表面)上的倾覆等压线中识别了 AWB 和 CWB。自组织图(SOM)是一种机器学习方法,用于将已识别的 RWB 事件聚类为每种类型的原型模式或 "味道"。AWB和CWB味道捕捉了每个流线的θ最小值/最大值的变化以及流线侧面的局部经向θ梯度(∇θ)的变化。不同风味之间∇θ的大小和位置的变化对应于喷流结构的多样性,从而导致垂直运动模式和对流层-深层环流的差异。AWB(CWB)事件的一个子集与强(低)地面高压系统的发展和极端极向水汽输送有关。就 CWB 而言,许多事件发生在相似的地理区域,但不同类型的降水和水汽模式却大相径庭。我们的研究结果表明,RWB 对对流层影响的位置、类型和严重程度在很大程度上取决于 RWB 强度。
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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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