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The UW NearCasting Product

Instructors:

Scott Lindstrom

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Topic:

Archived Training

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Developed:

2010

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Last Updated:

2012

Introduction


The teletraining describes the University of Wisconsin CIMSS’ NearCasting product, which is derived from Lagrangian model output. The variable that is predicted by the model is equivalent potential temperature at multiple levels. Thus, the model produces near-term forecasts of convective destabilization.

Outline:

  1. Bridges the gap between observations and forecast output
  2. Use of Sounder data in the NearCast model
  3. When and how NearCasting output should be used
  4. Examples
  5. AWIPS Installation procedures

This is an experimental GOES-R Proving Ground Product designed to foster GOES-R readiness.

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 Learn Center

  1. Audio playback (recommended for low-bandwidth users) – This is an audio playback version in the form of a downloadable VISITview and can be taken at anytime.

    Create a directory to download the audio playback file (246 MB) from the following link: http://rammb.cira.colostate.edu/training/visit/training_sessions/the_uw_nearcasting_product/the_uw_nearcasting_product_audio.exe

    After extracting the files into that directory click on either the visitplay.bat or visitauto.bat file to start the lesson. If both files are present, use visitauto.bat

References/Additional Links


  • Talking points are available for this lesson and may be printed out to easily review the session in detail at any time.
This course is Basic

There are no prerequisites

Contact

Scott Lindstrom

scottl@ssec.wisc.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.