Abstract
Toward developing efficient algorithms of geometric data mining, we extract extreme phenomena
with strong vortex of wind such as tropical cyclone (TC) from a meteorological database. The
database consists of observational values of some attributes, including wind vectors, at altitudes of certain
atmospheric pressure (17 levels) over circa 10,000 grid points on the earth. Conventional method regards
a grid point which fulfills some empirical conditions defined for a part of the pressure levels as the center
of a typhoon. So, it cannot detect extreme phenomenon with strong wind in another level than the ones
for which the empirical conditions are defined. Moreover, because the conventional method checks all
grid points, its computation costs enormously. In this study, we propose finding first centers of vortex by
moving from random initial positions along streamlines. Next, we calculate intensity and both horizontal
and vertical ranges of influence around each center of vortex, then, rank them in order of risk. Comparison
experiments showed that the proposed method found and ranked all typhoons extracted by the conventional
method as at high risk. Also, the proposed method detected some risky and possibly risky vortices
which the conventional method could not find.
