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GOES-R Pre-convective environment

Instructors:

Dan Bikos

Chris Gitro

Erin Dagg

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Topic:

Sat FC-G

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Developed:

2016

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Last Updated:

2018

Introduction


This module is part of the satellite foundational course for GOES-R (SatFC-G). This particular module introduces GOES-R capabilities for identification of the pre-convective environment. Specific topics include surface conditioning (differential heating), the elevated mixed layer (EML) and elevated cold fronts.

Since the size of this module is greater than 100 MB, we recommend that you utilize either the Download video OR YouTube version below.

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 that can be taken at anytime (streamed, not recommended for low-bandwidth users). Be sure to have your speakers on and the volume loud enough to hear the presentation.
  2. YouTube video:

  3. Download video (recommended for low-bandwidth users) – This is an audio playback version in the form of an Articulate Presenter video and can be taken at anytime.Create a directory to download the video file from the following link: http://rammb.cira.colostate.edu/training/visit/training_sessions/goes_r_pre_convective_environment/goes_r_pre_convective_environment_articulate.zip

    After extracting the files into that directory click on either the presentation.html OR index.html file and the video will begin to play in your browser.

Original Pre-Launch Version


This version of the training module debuted in the Fall of 2016 which included Himawari and pre-GOES-R era GOES imagery. Formats include:

References/Additional Links

This course is Basic

There are no prerequisites

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.