Skip to main content
U.S. flag

An official website of the United States government

Dot Gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

HTTPS

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Development of An Automated Approach For Identifying Convective Storm Type Using Reflectivity-derived and Near-storm Environment Data

Abstract

Extending storm classification into a separation of convective storm types has applications to nowcasting, severe weather warning and quantitative precipitation estimation and forecasting. This work presents an exploration of an automated classification scheme that uses a combination of radar reflectivity products and near-storm environmental parameters derived from Rapid Update Cycle (RUC) model analyses to assign one of eight classes to each storm observed. An assessment is made of the classification accuracy, and it is found that the scheme that uses the combination of radar and model data outperforms the scheme that uses only radar products. This is particularly notable in the identification of storms that have rotation, and therefore improves the assessment of those storms' potential longevity and severe weather threat.

Article / Publication Data
Active/Online
YES
Volume
116
Available Metadata
Accepted On
February 12, 2012
DOI ↗
Fiscal Year
Publication Name
Atmospheric Research
Published On
January 01, 2012
Final Online Publication On
February 01, 2012
Publisher Name
Elsevier
Print Volume
116
Page Range
67-81
Submitted On
February 17, 2011
URL ↗

Institutions

Not available

Authors

Authors who have authored or contributed to this publication.

Not available