Thursday, 13 February 2003: 5:15 PM
Motion estimator based on hierarchical clusters
In this paper, we describe the use of statistically
derived hierarchical clusters of weather data
to derive movement estimates from pairs of frames
in a time sequence. We show that the use of hierarchical
clusters enables small cells to be tracked
over short periods of time while using
the movement of the larger scale features
they are embedded in for longer periods.
The motion estimator has been applied both to reflectivity data
obtained from the National Weather
Service Radar (WSR-88D) and to cloud-top infrared temperatures
obtained from the GOES-11 satellite. We demonstrate the
results on both these sensors.