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.
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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.
Length: 90 minutes
Delivery: online module with audio and downloadable VISIT session with audio and talking points
Target Audience: Forecaster – although it is informative for all.
Addresses: Why, When, How, and What of GOES-R. The first third of the module discusses improvements to the GOES-R sensors over the current GOES sensors, and the rest of the module presents examples. To give a preview of ABI capabilities, examples are drawn from the European satellite Meteosat Second Generation (MSG) and the polar orbiting sensor Moderate Resolution Imaging Spectroradiameter (MODIS). The module can be viewed alone or taken as part of the SHyMet for Forescaster Series.
Example from module demonstrating a Red/Green/Blue (RGB) product from METEOSAT Second Generation visible and near infrared channels to highlight ice versus water cloud, snow versus background surface, and dust cloud.
Example from module demonstrating a false Red/Green/Blue (RGB) product for fire and smoke detection using the brightness temperature difference product (BT 3.9µm – BT 11.0 µm) to locate active hot fires and the 0.8 and 0.6 µm channels to highlight green vegetation versus burned areas and smoke areas.
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.
Length: 60 minutes
Delivery: teletraining and online module with audio
Target Audience: Forecaster
Addresses: GOES-R synthetic imagery for 2 water vapor channels at 6.95 um and 7.34 um and the long wave infrared at 10.35 um is produced from output of the NSSL 4-km WRF-ARW model by post-processing the certain model output fields through a radiance observation operator. In this module, 12 case days have been collected to compare GOES-R synthetic imagery with similar water vapor and infrared channels currently available on the GOES imager as well as other GOES channels, model information and conventional observations. The current GOES water vapor channels used for comparison are at 6.5 um on GOES 13 and at 6.7 um on GOES 11, and the current GOES infrared channel used for comparison is at 10.7 um. The sounder water vapor channel at 7.4 um is also used for feature identification and comparison with the synthetic imagery. The main role of the synthetic water vapor imagery is identifying shortwaves and jet streaks that may play a role in the initiation, maintenance and intensity of convection. The synthetic infrared imagery is useful for cloud coverage forecasts to assess insolation potential. The primary motivation for looking at synthetic imagery is that you can see many processes in an integrated way compared with looking at numerous model fields and integrating them mentally.
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.
Length: 30 minutes
Delivery: teletraining and online module with audio
Target Audience: Forecaster
Addresses: GOES-R synthetic imagery for the water vapor channel at 6.95 um and the long wave infrared at 10.35 um is produced from output of the NSSL 4-km WRF-ARW model by post-processing the certain model output fields through a radiance observation operator. Four examples are presented to compare GOES-R synthetic imagery with similar water vapor and infrared channels currently available on the GOES imager, as well as other GOES channels, other model output fields and surface observations. The current GOES water vapor channels used for comparison are at 6.5 um on GOES 13 and at 6.7 um on GOES 11, and the current GOES infrared channel used for comparison is at 10.7 um. Synthetic imagery analysis in forecasting orographic cirrus has a significant advantage compared to looking at model output fields such as relative humidity, in that the orographic cirrus appears similar to the way you are used to diagnosing it (with GOES). The cases demonstrate how to blend synthetic imagery with model output fields from multiple models to forecast temperature when there is potential for orographic cirrus.
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.
Length: 75 minutes
Delivery: teletraining and online module with audio
Target Audience: Forecaster
Addresses: This module highlights the 6.5 / 6.7 um water vapor channel available on current GOES 13 and 11 respectively as well as the 7.4 um water vapor channel currently available on the GOES sounder in forecasting severe weather events. The 7.4 um water vapor channel is utilized to highlight mid-level jet streaks and for tracking the elevated mixed layer in certain situations. This channel will be on GOES-R (at 7.34 um) at a much higher resolution then the current GOES sounder, so that it will be much more readily applicable for severe weather forecasting. Synthetic imagery from the NSSL 4-km WRF-ARW model is highlighted to demonstrate the improved spatial and temporal resolution that will be available with GOES-R.
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.
Length: 140 minutes
Delivery: online module with audio and talking points
Target Audience: Forecaster – although it is informative for all.
Addresses: This module introduces volcano hazards, starting with a geologic overview of the three main types of volcanoes (Cinder Cones, Composite Volcanoes, and Shield Volcanoes), two general eruption types (effusive and explosive), and three primary eruption mechanisms (magmatic, phreatic, and phreatomagmatic). The next section presents the monitoring methodology used to detect eminent volcanic activity. This is followed by a discussion of health hazards, aviation hazards, and methods to detect ash and aerosol in real time from satellite, aircraft, and ground-based (lightning, radar, and lidar) sensors. Many examples are shown to highlight detection of ash and aerosol by various satellite platforms and techniques and include comments on strengths and weaknesses of the approaches. The final section is devoted to modeling the movement of ash and aerosol and forecasting its dispersion. To drive home the point that the continental US has potential volcanic ash hazards, dispersion examples are given for 5 volcano regions in the western US.
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.
Length: 90 minutes
Delivery: online module with audio and talking points
Target Audience: Forecaster – although it is informative for all.
Addresses: The module begins with an example of the 2009 eruption of Alaska’s Mt. Redoubt volcano. It is followed by an overview of the key organizations involved in monitoring, detecting, and tracking volcano activity and volcanic hazards. It discusses the flow of information through these organizations during a volcano event. It also evaluates scientific and technical detection of ash and implications for air traffic control issues associated with the 2010 eruption of the Islandic volcano Eyjafjallajökull. The final section takes a look into future products for ash and aerosol detection. It ends with an example of synthetically produced RGB imagery of a hypothetical volcanic eruption from the Yellowstone, Wyoming region.
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.
Length: 50 minutes
Delivery: online module with audio and downloadable VISIT session with audio and talking points
Target Audience: Forecaster
Addresses: This module discusses simple methods to calculate visible and infrared cloud composites and presents various ways to composite the information: diurnally, monthly, seasonally, annually, by regime, and by event. Examples are presented from a sea breeze study at the Tallahassee, Florida WFO, a strong wind event study at the Cheyenne, Wyoming WFO and a marine stratus study at the Eureka, California WFO.