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Data Fusion techniques for Low-Topped Severe Thunderstorm Events

Instructors:

Dan Bikos

Jim LaDue

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Topic:

Severe

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Developed:

2022

Introduction


This training session will build on data fusion methodologies from the Data Fusion section of the WOC Severe Course (updated in FY21). We will apply these data fusion concepts to the particularly challenging scenario of low-topped severe thunderstorms. Two case studies are presented, the primary learning objective is to examine how the four data fusion considerations manifested themselves in these cases. The motivation for doing this is to strive for a proactive approach to severe weather warnings rather than being reactive.

 

Training Session Options


NOAA/NWS students – to begin the training, use the web-based video, YouTube video, or audio playback options below (if present for this session). Certificates of completion for NOAA/NWS employees can be obtained by accessing the session via the Commerce Learning Center.

  1. Web-based video

References/Additional Links


This course is Advanced

The Data Fusion section of the WOC Severe Track FY21 update is a prerequisite to this training.  Under the Data Fusion section, see the two “Practice and Applications from Multiple Data Sources” training sessions.

Contact

Dan Bikos

Dan.Bikos@colostate.edu

Page Contact

Bernie Connell

bernie.connell@colostate.edu

970-491-8689

Unless otherwise noted, all content on the CIRA RAMMB: VISIT, SHyMet and VLab webpages are released under a Creative Commons Attribution 3.0 License.