Click on the thumbnail images or links below to launch/redirect to each training course.
Virtual Institute for Satellite Integration Training (VISIT) is a joint effort involving NOAA Cooperative Institutes, the National Environmental Satellite Data and Information Service (NESDIS), and the National Weather Service (NWS). The primary mission of VISIT is to accelerate the transfer of research results based on atmospheric remote sensing data into NWS operations using distance education techniques. Training sessions include topics on satellite meteorology, severe weather, climate, numerical weather prediction, and more.
Many of these modules were developed in collaboration with the Cooperative Institute for Meteorological Satellite Studies (CIMSS) and the Cooperative Institute for Research in the Atmosphere (CIRA). VISIT also provides satellite chats to demonstrate satellite products that can be applied to operational forecasting and identify new training topics based on specific participant needs. See the VISIT Training Calendar for upcoming teletraining sessions.
VISIT offers a wide selection of satellite remote sensing training materials. See the VISIT Training Sessions webpage for a complete listing.
The National Weather Service Forecast Decision Training Division (FDTD) Satellite Application Webinars are peer-to-peer learning; staff from Weather Forecast Offices (WFOs), National Centers, Center Weather Service Units (CWSUs), and River Forecast Centers (RFCs) lead the presentations. The webinars to share how to apply GOES imagery with other datasets for a specific operational application.
SHyMet: Satellite Foundational Course for GOES-R/16: This National Weather Service (NWS) Satellite Foundation Course for GOES-R/16 contains 37 short training modules to bring forecasters, the scientific community, and others up-to-date on the capabilities of the GOES-R/GOES-16 satellite.
SHyMet Severe Thunderstorm Forecasting: The Severe Thunderstorm Forecasting track of the SHyMet course covers how to integrate satellite imagery interpretation with other datasets in analyzing severe thunderstorm events.