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GOES-R – Risk Reduction – Training

When the data are flowing from GOES-R in 2015+, will we be ready? YES – because we are starting our training efforts now. The training efforts leverage the existing VISIT and SHyMet structure.


GOES-R 101

Presents a brief overview of the sensors that will be on GOES-R and includes those for Space Weather, Auxiliary Services, the Geostationary Lightning Mapper, and the Advanced Baseline Imager.

Synthetic Imagery in Forecasting Severe Weather

This module examines many examples which demonstrate how to effectively use GOES-R synthetic water vapor and infrared imagery from the NSSL 4-km WRF-ARW model in forecasting severe weather.

Synthetic Imagery in Forecasting Orographic Cirrus

This module highlights the advantages of using GOES-R synthetic (WV or IR) imagery from the NSSL 4-km WRF-ARW model to forecast the occurrence of orographic cirrus and its associated effects on surface temperature forecasting.

The following modules include embedded GOES-R content

Water Vapor Imagery Analysis for Severe Weather

The primary objective of this session is to maximize the information available from the GOES water vapor imagery during severe weather episodes, and how to effectively utilize this information with other available datasets.

Volcanoes and Volcanic Ash (Part 1)

This module gives a brief overview of volcano types and associated hazards on the ground and in the air. It discusses remote sensing techniques of ash and aerosol detection as well as modeling and plume dispersion.

Volcanoes and Volcanic Ash (Part 2)

This module follows the information content of part 1 by presenting examples of ash and aerosol detection and model dispersion output. It introduces the key organizations involved in monitoring, detecting, and tracking volcano activity and volcanic hazards and what their responsibilities are.

Regional Satellite Cloud Composites from GOES

This module describes what a regional satellite cloud composite is, what types of simple cloud composites can be created from GOES imagery, and how they can be used in the forecast process.