Storm Tracking and Monitoring Using Objective Synoptic Diagnosis and Cluster Identification from Infrared Meteosat Imagery: A Case Study |
| |
| Authors: | M C Llasat C Ramis L Lanza |
| |
| Institution: | (1) Department of Astronomy and Meteorology, University of Barcelona, Spain, ES;(2) Department of Physics, University of Balearic Islands, Palma de Mallorca, Spain, ES;(3) Department of Environmental Engineering, University of Genoa, Italy, IT |
| |
| Abstract: | Summary The present paper investigates the potential of combining image processing techniques based on cluster analysis of infrared
(IR) Meteosat images with dynamic meteorological theory on synoptic systems. From this last point of view the highest probability
of deep convective development is favoured where the overlapping of four mechanisms acting at synoptic scale is produced:
upward quasi-geostrophic forcing, convergence of water vapour at low levels, convective instability in the lower troposphere
and great convective available potential energy. Cloud tracking is performed over sequences of Meteosat IR images by using
a shape parameterisation approach after appropriate filtering for non-significant clouds and automated identification of convective
systems. The integrated methodology is applied to the case study of the heavy rainfall event which produced floods in the
South of France and the North of Italy on September 27–28th, 1992. The analysis focuses on the monitoring and explanation of the zones most affected by heavy rainfall with the aim of
investigating possible improvements of the predictive potential of cloud tracking and allowing identification of the areas
which most lend themselves to flash floods for use in operational flood forecasting applications.
Received July 20, 1998/Revised June 21, 1999 |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
