scholarly journals The extratropical transition of Hurricane Ophelia (2017) as diagnosed with a generalized omega equation and vorticity equation

2020 ◽  
Vol 72 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Mika Rantanen ◽  
Jouni Räisänen ◽  
Victoria A. Sinclair ◽  
Juha Lento ◽  
Heikki Järvinen
Tellus ◽  
1955 ◽  
Vol 7 (4) ◽  
pp. 518-521 ◽  
Author(s):  
N. P. Fofonoff ◽  
R. B. Montgomery

2018 ◽  
Vol 146 (12) ◽  
pp. 4279-4302 ◽  
Author(s):  
Alex M. Kowaleski ◽  
Jenni L. Evans

Abstract An ensemble of 72 Weather Research and Forecasting (WRF) Model simulations is evaluated to examine the relationship between the track of Hurricane Sandy (2012) and its structural evolution. Initial and boundary conditions are obtained from ECMWF and GEFS ensemble forecasts initialized at 0000 UTC 25 October. The 5-day WRF simulations are initialized at 0000 UTC 27 October, 48 h into the global model forecasts. Tracks and cyclone phase space (CPS) paths from the 72 simulations are partitioned into 6 clusters using regression mixture models; results from the 4 most populous track clusters are examined. The four analyzed clusters vary in mean landfall location from southern New Jersey to Maine. Extratropical transition timing is the clearest difference among clusters; more eastward clusters show later Sandy–midlatitude trough interaction, warm seclusion formation, and extratropical transition completion. However, the intercluster variability is much smaller when examined relative to the landfall time of each simulation. In each cluster, a short-lived warm seclusion forms and contracts through landfall while lower-tropospheric potential vorticity concentrates at small radii. Despite the large-scale similarity among the clusters, relevant intercluster differences in landfall-relative extratropical transition are observed. In the easternmost cluster the Sandy–trough interaction is least intense and the warm seclusion decays the most by landfall. In the second most eastward cluster Sandy retains the most intact warm seclusion at landfall because of a slightly later (relative to landfall) and weaker trough interaction compared to the two most westward clusters. Nevertheless, the remarkably similar large-scale evolution of Sandy among the four clusters indicates the high predictability of Sandy’s warm seclusion extratropical transition before landfall.


1975 ◽  
Vol 19 (1) ◽  
pp. 102-103
Author(s):  
Vojtěch Vítek ◽  
O. Zikmunda
Keyword(s):  

2012 ◽  
Vol 376 (14) ◽  
pp. 1179-1184 ◽  
Author(s):  
Alexander Bihlo ◽  
Roman O. Popovych

AIAA Journal ◽  
2000 ◽  
Vol 38 (5) ◽  
pp. 774-783 ◽  
Author(s):  
Stephen A. Huyer ◽  
John R. Grant

2016 ◽  
Vol 30 (1) ◽  
pp. 67-75
Author(s):  
Xiuming Wang ◽  
Xiaogang Zhou ◽  
Zuyu Tao ◽  
Hua Liu

2008 ◽  
Vol 21 (4) ◽  
pp. 788-801 ◽  
Author(s):  
Jee-Hoon Jeong ◽  
Baek-Min Kim ◽  
Chang-Hoi Ho ◽  
Yeon-Hee Noh

Abstract The variations in the wintertime precipitation over East Asia and the related large-scale circulation associated with the Madden–Julian oscillation (MJO) are examined. By analyzing the observed daily precipitation for the period 1974–2000, it is found that the MJO significantly modulates the distribution of precipitation over four East Asian countries; the precipitation rate difference between wet and dry periods over East Asia, when the centers of MJO convective activities are located over the Indian Ocean and western Pacific, respectively, reaches 3–4 mm day−1, which corresponds to the climatological winter-mean value. Composite analysis with respect to the MJO suggests that the MJO–precipitation relation is mostly explained by the strong vertical motion anomalies near an entrance region of the East Asia upper-tropospheric jet and moisture supply in the lower troposphere. To elucidate different dynamic origins of the vertical motion generated by the MJO, diagnostic analysis of a generalized omega equation is adopted. It is revealed that about half of the vertical motion anomalies in East Asia are induced by the quasigeostrophic forcings by the MJO, while diabatic heating forcings explain a very small fraction, less than 10% of total anomalies.


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