Detecting Comma-shaped Clouds for Severe Weather Forecasting using Shape and Motion

Xinye Zheng (1), Jianbo Ye (1), Yukun Chen (1), Stephen Wistar (2),
Jia Li (1), Jose A. Piedra-Fernandez (3), Michael A. Steinberg (2), James Z. Wang (1)
(1) The Pennsylvania State University, USA
(2) Accuweather Inc., USA
(3) University of Almeria, Spain

Meteorologists use shapes and movements of clouds in satellite images as indicators of several major types of severe storms. Satellite imaginary data are in increasingly higher resolution, both spatially and temporally, making it impossible for humans to fully leverage the data in their forecast. Automatic satellite imagery analysis methods that can find storm-related cloud patterns as soon as they are detectable are in demand. We propose a machine learning and pattern recognition based approach to detect "comma-shaped" clouds in satellite images, which are specific cloud distribution patterns strongly associated with the cyclone formulation. In order to detect regions with the targeted movement patterns, our method is trained on manually annotated cloud examples represented by both shape and motion-sensitive features. Sliding windows in different scales are used to ensure that dense clouds will be captured, and we implement effective selection rules to shrink the region of interest among these sliding windows. Finally, we evaluate the method on a hold-out annotated comma-shaped cloud dataset and cross-match the results with recorded storm events in the severe weather database. The validated utility and accuracy of our method suggest a high potential for assisting meteorologists in weather forecasting.

Full Paper
(high-resolution PDF, 25MB)

Full Paper
(reduced-resolution PDF, 3.6MB)

More information

Citation: Xinye Zheng, Jianbo Ye, Yukun Chen, Stephen Wistar, Jia Li, Jose A. Piedra-Fernandez, Michael A. Steinberg and James Z. Wang, ``Detecting Comma-shaped Clouds for Severe Weather Forecasting using Shape and Motion,'' IEEE Transactions on Geoscience and Remote Sensing, 13 pages, 2018, under second-round review.

© 2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Last Modified: February 28, 2018
© 2018