Statistical Reconstruction of Seasonal Tropical Cyclone Variability in the North Atlantic Basin

被引:2
|
作者
Titus, Matthew Lee [1 ,2 ]
Thompson, Keith R. [3 ]
Oliver, Eric C. J. [3 ]
Klotzbach, Philip J. [4 ]
机构
[1] Environm & Climate Change Canada, Dartmouth, NS, Canada
[2] Dalhousie Univ, Dept Phys & Atmospher Sci, Halifax, NS, Canada
[3] Dalhousie Univ, Dept Oceanog, Halifax, NS, Canada
[4] Colorado State Univ, Ft Collins, CO 80523 USA
基金
加拿大自然科学与工程研究理事会;
关键词
North Atlantic; redundancy analysis; seasonal prediction; tropical cyclones;
D O I
10.1029/2020JD032669
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Seasonal forecasting of tropical cyclones is a topic of considerable interest to the public, government and private sectors. To improve understanding of the dynamics controlling the predictability of tropical cyclone (TC) activity, and improve the accuracy of forecasts, multiple studies have related TC activity to empirically-defined indices including the El Nino-Southern Oscillation, the Atlantic Multidecadal Oscillation, and the North Atlantic Oscillation. These indices were not developed to forecast TC activity but rather summarize other aspects of atmosphere-ocean variability. In this study we use a statistical approach, based on redundancy analysis, to define two indices related to overall activity and steering of TCs. We focus on North Atlantic TCs that reached tropical storm strength (>= 34 kt) between August and October 1948-2016. TC occurrences are binned using an equal area grid that covers the North Atlantic. The redundancy indices are linear combinations of mean sea level pressure for the same season. Cross validation is used to guard against over fitting in the definition of the indices. This approach provides two physically interpretable redundancy indices related to North Atlantic TC activity. The leading redundancy index is used to successfully reconstruct the total number of TCs and the accumulated cyclone energy, over the extended period 1878-2014 using seasonal mean sea level pressures from the National Centers for Environmental Prediction 20th-Century Reanalysis version 2c. Extensions of the approach for seasonal forecasting are discussed.
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收藏
页数:17
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