Optimal tropical cyclone size parameter for determining storm-induced maximum significant wave height
Main question: what part of the TC actually builds the largest waves?
Main claim: the largest TC generated waves are controlled much more by the broad region of moderately strong winds (represented by R34) than by the compact region of peak winds near the eyewall (represented by RMW)
Narrative: extended fetch framework -> test RMW as metric -> poor results -> show R34 is dynamically better -> explain through cumulative wind forcing
Introduction
matters!
Physical framework: Extended fetch- in the right front quadrant of a TC: winds blow roughly in the same direction as storm motion waves move with the storm waves stay inside stronger winds longer Therefore: effective fetrch becomes much larger than the geometric fetch, creating the largest waves
Traditional assumption: Assume RMW means broader core, larger effective fetch and larger waves Thus, RMW became the standard TC size parameter
Challenge: Two storms can have identical max winds and identical translation speeds but have larger RMW and smaller wave heights
Figure 1:
105 TCs with kt
Case A -> large RMW
Case B -> small RMW
expectation: large RMW should produce larger waves
reality: case B produces larger waves (R34, R50, R64 are all higher, the storm contains more total wind energy)
Methods
Data 642 Atlantic hurricanes from 1988-2017
Model WWIII to simulate wavew fields generated by idealized moving hurricanes
Storm design choices: symmetric have fixed translation speeds fixed intensities so that the role of storm size can be isolated
Section 3
Figure 2:
composite wave field from all strong hurricanes
depicts crescent shaped high wave region in the front right quadrant
confirms extended fetch analysis, largest waves occur where the storm motion and wind align
Key point: the highest waves occur near RMW but the largest variability does not.
The strongest sensitivity actually occurs between the RMW and R50 lines, hinting at the importance of broader wind structure
Figure 3:
Correlation of with different size metrics
A & D (RMW) -> weak
B & E (R34) -> strong
C & F (R50) -> intermediate
If RMW really controlled wave growth, these panels should have the strongest correlations. Instead, they are the weakest.
Key Point: the storm’s outer circulation predicts max wave height far better
Figure 4: Same analysis but for faster moving storms Fast moving storms benefit most from extended fetch -> storm size metrics that describe the full wind field become even more important
Figure 5:
Spatial maps of correlation between local and RMW, R34, R50
RMW -> correlation only exists in limited regions
R34 -> strong positive correlation almost everywhere
R34 doesn’t just explain the peak wave, it explains the entire wave field.
Figure 6:
Accumulated wind = sum of wind components aligned with storm motion -> integrated wind forcing
vs accumulated wind -> huge correlation
The waves respond to how much forcing they experience over time, not the peak value
wave states reflect integrated forcing hsitory and organization, not just instantaneous wind speed
Figure 7: Correlation between accumulated wind and RMW, R34 and R50 R34 is the highest again R34 represents accumulated wind which captures -> RMW does not control accumulated wind, therefore it doesn’t control either
Case Study
Case A: large RMW, small R34 Case B: small RWM, large R34
Case B: strong winds extending farther outward -> wave field experiences much larger effective fetch contains stronger winds and more large waves
(figure 8,9)
Figure 10: relationship between storm intensity and size metrics RMW -> negative correlation (stronger storms have smaller RMW) R34 -> positive correlation (stronger storms have larger R34)
Conclusions
- RMW is not the optimal hurricane size metric for wave prediction (despite decades of use)
- R34 is substantially better
- Max waves are controlled by integrated wind forcing
Relevance to my research
Their result: wave state is determined by the spatial organization of forcing, not just peak forcing. My result: high frequency spectral structure is determined by the organization and history of forcing, not just bulk wave state The ocean surface remembers integrated dynamical structure. Two systems can have the same local metrics while occupying different dynamical states because of differences in how forcing distributed through space and time.
Shift in discussion from storm geometry -> integrated forcing history (deeper physical explanation)