An Objective Model for Identifying Secondary Eyewall Formation in Hurricanes

被引:127
作者
Kossin, James P. [1 ]
Sitkowski, Matthew [1 ]
机构
[1] Univ Wisconsin, Cooperat Inst Meteorol Satellite Studies, Madison, WI 53706 USA
关键词
PREDICTION SCHEME SHIPS; NUMERICAL-SIMULATION; WIND MAXIMA; PART I; INTENSITY; SKILL; EVOLUTION; ATLANTIC; CYCLE;
D O I
10.1175/2008MWR2701.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Hurricanes, and particularly major hurricanes, will often organize a secondary eyewall at some distance around the primary eyewall. These events have been associated with marked changes in the intensity and structure of the inner core, such as large and rapid deviations of the maximum wind and significant broadening of the surface wind field. While the consequences of rapidly fluctuating peak wind speeds are of great importance, the broadening of the overall wind field also has particularly dangerous consequences in terms of increased storm surge and wind damage extent during landfall events. Despite the importance of secondary eyewall formation in hurricane forecasting, there is presently no objective guidance to diagnose or forecast these events. Here a new empirical model is introduced that will provide forecasters with a probability of imminent secondary eyewall formation. The model is based on environmental and geostationary satellite features applied to a naive Bayes probabilistic model and classification scheme. In independent testing, the algorithm performs skillfully against a defined climatology.
引用
收藏
页码:876 / 892
页数:17
相关论文
共 58 条
  • [1] [Anonymous], 2006, INT GEOPHYS SERIES
  • [2] Bellman R. E., 1957, Dynamic programming. Princeton landmarks in mathematics
  • [3] Bishop Christopher M, 1995, Neural networks for pattern recognition
  • [4] Dissipative heating and hurricane intensity
    Bister, M
    Emanuel, KA
    [J]. METEOROLOGY AND ATMOSPHERIC PHYSICS, 1998, 65 (3-4) : 233 - 240
  • [5] BLACK ML, 1992, MON WEATHER REV, V120, P947, DOI 10.1175/1520-0493(1992)120<0947:TCECOH>2.0.CO
  • [6] 2
  • [7] Incorporating misclassification error in skill assessment
    Briggs, W
    Pocernich, M
    Ruppert, D
    [J]. MONTHLY WEATHER REVIEW, 2005, 133 (11) : 3382 - 3392
  • [8] Assessing the skill of yes/no predictions
    Briggs, W
    Ruppert, D
    [J]. BIOMETRICS, 2005, 61 (03) : 799 - 807
  • [9] Camp JP, 2001, MON WEATHER REV, V129, P1704, DOI 10.1175/1520-0493(2001)129<1704:HMIPAP>2.0.CO
  • [10] 2