Morphometric analysis of tropical storm and hurricane tracks in the North Atlantic basin using a sinuosity‐based approach

Abstract

Quantitative analysis is carried on the shape of over 420 tropical storm and hurricane tracks in the North Atlantic basin for the period 1965–2011. A sinuosity metric is used as the basis for track morphometry, applied to best‐track data accessed from the IBTrACs archive maintained by NOAA. GIS tools, track mapping according to sinuosity category, and various statistical analyses permit temporal and spatial patterns in track shape to be identified and investigated. Temporal analysis reveals no underlying long‐term trend in track sinuosity over the past 4.5 decades, implying an absence of climatic‐change forcing on storm migration behaviour at the basin scale. Instead, large inter‐annual variability dominates, although it is possible to observe episodes of notable cyclic swings in average sinuosity towards straighter or more sinuous tracks. Seasonality in track behaviour is pronounced, as similarly reported for other ocean basins. Predictable straight and quasi‐straight track types are more common (64–100%) during the early months (May to July) of the hurricane season, with this reversing at the peak and later phase of the season (September, November) to a predominance for quasi‐sinuous and sinuous tracks (58–70%). In spatial terms, track morphometric analysis according to 10° longitudinal zone of cyclogenesis is valuable, revealing that storm origin is reasonably indicative of likely track shape over the subsequent lifespan. Thus, while 62–68% of storms spawned west of 80°W in the Caribbean Sea – Gulf of Mexico region show a tendency to follow straighter tracks, 67–72% of storms formed east of 40°W in the central‐eastern North Atlantic subsequently describe more sinuous tracks. Overall, these patterns are seen to influence the geographic potential of storm landfall. This is important for societal vulnerability on coastlines at risk, since storms exhibiting higher track sinuosity generally prove to survive longer, migrate farther and therefore display greater potential for inflicting damage over wider areas.

Variability of southwest Pacific tropical cyclone track geometry over the last 70 years

“…This cluster is consistent with Ramsay et al (2012) who also identified a cluster located in the similar region (with comparable characteristics) and demonstrated the influence of EN and LN on these TCs. Our findings (of Cluster 2 events) also corresponds with notable EN phases and seasons with highest TC counts such as 1981, 1983, 1998, and 2015-2016, reflected in Figures 4a,c, respectively (Yu and Kim, 2013. The TC track regime of Cluster 2 (i.e., increasing trend in the eastern SWP with longer tracks) compares with Sharma et al (2020), given they reported on the east-to-northeasterly modulation of TC genesis and expansion of the decay region in a southeasterly direction.…”

“…Also, EN phases observed in Figure 4a align with the peaks observed along the Cluster 2 timeline, e.g. , 1981, , 1983, , 1998, and 2015, -2016. Figure 4e shows peaks in Cluster 4 TCs during 1964TCs during , 1985TCs during -1986 and 2016 and a statistically significant decreasing trend.…”

“…The study also investigated the sinuosity of TC tracks, based on track linearity and curvature. Consistent with Terry and Gienko (2011), Chand (2012), Terry et al 2013and Terry and Kim (2015), we carried out the calculation of sinuosity (S) and the sinuosity index (SI) using Equations (1) and (2), respectively: Sinuosity = Distance of TC track DisplacementTCtrack ð1Þ…”

“…The indexing of SI categories was then determined following the technique used by Terry and Gienko (2011), Terry et al (2013) and Terry and Kim (2015). After removing TC tracks with SI = 0, the remaining TCs in the data set with n = 859 (n = 593 for the 48-year period) were divided using the quartile ranges, ensuring that upper and lower halves of the distribution are separated by the central boundary, i.e., the median SI value.…”

Consecutive Dual-Vortex Interactions between Quadruple Typhoons Noru, Kulap, Nesat and Haitang during the 2017 North Pacific Typhoon Season

“…Accurately predicting the migratory track, intensity and rainfall of TCs is a key research focus for meteorologists and weather forecasters [9]. Factors influencing track orientation, shape, sinuosity, and ultimately points of landfall are of particular interest [10,11]. Satellite-based cloud images are useful for analyzing TC cloud structure and dynamics [12][13][14][15][16].…”