Forecaster Training for the GOES-R Fog/low stratus (FLS) Products
Scott Lindstrom, Mike Pavolonis and Corey Calvert
(1) Learn how the GOES-R Fog/Low Stratus product improves upon the traditional brightness temperature difference (BTD) product
(2) Understand how the GOES-R FLS product is created
(3) See examples of how the product should be used in different geographic regions.
(1) GOES-R ABI Introduction
(2) Fog / Low Stratus description and definition
(3) Traditional Fog Detection Methods and problems with them
(4) The GOES-R FLS Product and how it improves on traditional methods
This is a basic course. There are no prerequisites.
Training Session Options
LMS students - to begin the training, use the web-based video or audio playback options below (if present for this session).
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. Certificates of completion for NOAA employees can be obtained on the E-Learning Management System LMS
Create a directory to download the audio playback file (197 MB) from the following link: http://rammb.cira.colostate.edu/training/visit/training_sessions/forecaster_training_for_the_goes-r_fog_low_stratus_products/forecaster_training_for_the_goes-r_fog_low_stratus_products_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
- Live VISIT teletraining (with an instructor leading the session). Check the VISIT Training Calendar to signup for teletraining. The session will last 60 minutes. This teletraining session uses the VISITview software, where a Windows PC with an Internet connection is needed.
Please follow the teletraining installation instructions to install the session
- Talking points are available for this lesson and may be printed out to easily review the session in detail at any time.
Powerpoint version of training slides
GOES-R Fog Product Examples
- Developed: 2012