Objective identification of annular hurricanes

被引:26
作者
Knaff, John A. [1 ]
Cram, Thomas A. [2 ]
Schumacher, Andrea B. [3 ]
Kossin, James P. [4 ]
DeMaria, Mark [1 ]
机构
[1] Colorado State Univ, NOAA, NESDIS, Off Res & Applicat,CIRA,Ctr Satellite Applicat &, Ft Collins, CO 80523 USA
[2] Colorado State Univ, Dept Atmospher Sci, Ft Collins, CO 80523 USA
[3] Colorado State Univ, Cooperat Inst Res Atmosphere, Ft Collins, CO 80523 USA
[4] Univ Wisconsin, Cooperat Inst Meteorol Satellite Studies, Madison, WI USA
关键词
D O I
10.1175/2007WAF2007031.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Annular hurricanes are a subset of intense tropical cyclones that have been shown in previous work to be significantly stronger, to maintain their peak intensities longer, and to weaken more slowly than average tropical cyclones. Because of these characteristics, they represent a significant forecasting challenge. This paper updates the list of annular hurricanes to encompass the years 1995-2006 in both the North Atlantic and eastern-central North Pacific tropical cyclone basins. Because annular hurricanes have a unique appearance in infrared satellite imagery, and form in a specific set of environmental conditions, an objective real-time method of identifying these hurricanes is developed. However, since the occurrence of annular hurricanes is rare (similar to 4% of all hurricanes), a special algorithm to detect annular hurricanes is developed that employs two steps to identify the candidates: 1) prescreening the data and 2) applying a linear discriminant analysis. This algorithm is trained using a dependent dataset (1995-2003) that includes 11 annular hurricanes. The resulting algorithm is then independently tested using datasets from the years 2004-06, which contained an additional three annular hurricanes. Results indicate that the algorithm is able to discriminate annular hurricanes from tropical cyclones with intensities greater than 84 kt (43.2 m s(-1)). The probability of detection or hit rate produced by this scheme is shown to be similar to 96% with a false alarm rate of similar to 6%, based on 1363 six-hour time periods with a tropical cyclone with an intensity greater than 84 kt (1995-2006).
引用
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页码:17 / 28
页数:12
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