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2 Cooperative Institute for Meteorological Satellite Studies University of Wisconsin PowerPoint Presentation
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2 Cooperative Institute for Meteorological Satellite Studies University of Wisconsin

2 Cooperative Institute for Meteorological Satellite Studies University of Wisconsin

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2 Cooperative Institute for Meteorological Satellite Studies University of Wisconsin

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  1. Recent VISIT and SHyMet Training: Applications of Satellite Imagery and Products to Operational Forecasting Dan Bikos1, B. Connell1, E. Szoke1, S. Bachmeier2,S. Lindstrom2, T. Mostek3, M. DeMaria4, J. Braun SHyMet rammb.cira.colostate.edu/shymet The Satellite HydroMeteorology (SHyMet) course consists of a series of courses (Intern, Forecaster, Severe Weather, Tropical) that help satisfy achievement of NOAA and NWS goals under the Government Performance Results Act (GPRA). Users have claimed to need help because of the abundant training available. SHyMet solves this by packaging a number of indivudal training sessions into a single course. SHyMet courses leverage exist training sessions (VISIT, COMET etc.) organized into topics that students can easily identify. SHyMet training is delivered via audio / video playback modules (i.e., web-pages or recorded VISITview). GOES-R Proving Ground Training Course Coming Soon This is a new SHyMet course designed to gather all GOES-R Proving Ground related training into one course so that users can readily know where to find training related to GOES-R Proving Ground products. The new training sessions highlighted center will be contained in this new SHyMet course. VISIT rammb.cira.colostate.edu/visit/ The primary mission of the Virtual Institute for Satellite Integration Training (VISIT) is to accelerate the transfer of research results based on atmospheric remote sensing data into National Oceanic and Atmospheric Administration (NOAA) / National Weather Service (NWS) operations. This transfer is accomplished through the education of NWS forecasters on the latest techniques to integrate remote sensing data, especially from satellite, into the weather and forecasting process. New Training Sessions GOES-R Fog / Low Stratus Products By Mike Pavolonis and Corey Calvert Outline: (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 (5) Examples Types of Training 1. Live teletraining – an instructor leads a training session with participants via a conference phone line and the VISITview software. The VISITview software is a platform-independent distance learning and collaboration package that allows multiple users to simultaneously view and manipulate the same series of pages containing images, animations, graphics, and text. 2. Audio / video playback via web-pages – The instructor records the training and it is made available for all to view and listen to on VISIT web-pages. This type of training has become more popular since it is available for students to take at their own convenience. Target Audience Forecasters at each NWS operational office (National Center, Weather Forecast Office, River Forecast Center, and Central Weather Service Unit) and anyone else inside or outside NOAA who is interested. Synthetic Imagery in Forecasting Cyclogenesis By Dan Bikos This training session builds off the previous VISIT Cyclogenesis course which stressed a blend of conceptual models, NWP output and GOES satellite imagery. In this training session, the NWP output will be the synthetic imagery from the NSSL WRF-ARW model which will make for an efficient comparison between the NWP output and the GOES satellite imagery. The goal is to gauge how much confidence one should have in NWP output strictly from the cyclogenesis evolution perspective. VISIT Satellite Chat These are monthly online discussions that are done via conference call and gotomeeting. These interactive discussions are intended to: Be brief, about 30 minutes in length. Demonstrate satellite products that can be applied to operational forecasting. Exchange ideas across both operational and academic sides. Identify new training topics based on specific participant needs. Incorporate recent weather events and investigate real-time data. Recordings of each chat session are made available on the VISIT web-pages so that users may review them on their own time. Synthetic Imagery in Forecasting Low Clouds and Fog By Dan Bikos In this training session we consider applications of the synthetic imagery in forecasting low clouds and fog. 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. Objective Satellite-Based Overshooting Top and Enhanced-V Anvil Thermal Couplet Signature Detection By Scott Lindstrom Objectives: (1) Learn how satellite data can be used objectively to detect features associated with strong thunderstorms. (2) Learn how overshooting tops and thermal couplets are related to severe weather. • Blogs • VISIT • rammb.cira.colostate.edu/training/visit/blog/ • CIMSS Satellite • cimss.ssec.wisc.edu/goes/blog/ • GOES-R Proving Ground • rammb.cira.colostate.edu/research/goes-r/proving_ground/blog/ Synthetic Imagery in Forecasting Severe Weather By Dan Bikos In this training session we consider applications of the synthetic imagery towards severe weather events. 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. 4National Oceanic and Atmospheric Administration NOAA/NESDIS Satellite Applications Research Regional and Mesoscale Meteorology Branch Fort Collins, Colorado, USA Mark.Demaria@noaa.gov 1Cooperative Institute for Research in the Atmosphere Colorado State University Fort Collins, Colorado, USA Dan.Bikos@colostate.eduBernie.Connell@colostate.edu Edward.J.Szoke@noaa.gov 2Cooperative Institute for Meteorological Satellite Studies University of Wisconsin Madison, Wisconsin, USA scottl@ssec.wisc.edu Scott.Bachmeier@ssec.wisc.edu 3National Oceanic and Atmospheric Administration National Weather Service Training Division Boulder, Colorado, USA Anthony.Mostek@noaa.gov Acknowledgments This work is supported by NOAA Grant: NA090AR4320074