Simulation of Atlantic Hurricane Tracks and Features: A Deep Learning
Approach
- URL: http://arxiv.org/abs/2209.06901v1
- Date: Fri, 12 Aug 2022 13:14:25 GMT
- Title: Simulation of Atlantic Hurricane Tracks and Features: A Deep Learning
Approach
- Authors: Rikhi Bose, Adam L. Pintar, and Emil Simiu
- Abstract summary: This paper employs machine learning (ML) and deep learning (DL) techniques to obtain from input data (storm features) available in or derived from the HURDAT2 database models.
In pursuit of this objective, a trajectory model providing the storm center in terms of longitude and latitude, and intensity models providing the central pressure and maximum 1-$min$ wind speed at 10 $m$ elevation were created.
The efficacy of the storm simulation models is demonstrated for three examples: New Orleans, Miami and Cape Hatteras.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The objective of this paper is to employ machine learning (ML) and deep
learning (DL) techniques to obtain from input data (storm features) available
in or derived from the HURDAT2 database models capable of simulating important
hurricane properties such as landfall location and wind speed that are
consistent with historical records. In pursuit of this objective, a trajectory
model providing the storm center in terms of longitude and latitude, and
intensity models providing the central pressure and maximum 1-$min$ wind speed
at 10 $m$ elevation were created. The trajectory and intensity models are
coupled and must be advanced together, six hours at a time, as the features
that serve as inputs to the models at any given step depend on predictions at
the previous time steps. Once a synthetic storm database is generated,
properties of interest, such as the frequencies of large wind speeds may be
extracted from any part of the simulation domain. The coupling of the
trajectory and intensity models obviates the need for an intensity decay inland
of the coastline. Prediction results are compared to historical data, and the
efficacy of the storm simulation models is demonstrated for three examples: New
Orleans, Miami and Cape Hatteras.
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