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Hongli Jiang, Steve Albers, Yuanfu Xie, Zoltan Toth, Isidora Jankov, Michael Scotten, Joseph Picca, Greg Stumpf, Darrel Kingfield, Daniel Birkenheuer, and Brian Motta

2013 [animation of 1-km vLAPS/ARW 2-h forecast for simulated Moore tornado is shown in the online supplement (DOI: 10.1175/BAMS-D-13-00185.2 )]. Camera image is not available for comparison for the simulated Moore tornado storm. The comparison of observed and simulated all-sky images can also assist the development of high-resolution analysis and vLAPS/ARW forecast products. This technique helped, for example, to improve the consistency of cloud albedo and microphysical variables, and to reduce

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Robert Gall, James Franklin, Frank Marks, Edward N. Rappaport, and Frederick Toepfer

. The progress of Stream 2 work is evaluated each off-season to identify techniques that appear particularly promising to operational forecasters and/or modelers. These potential advances can be blended into the operational implementation plans through subsequent Stream 1 activities, or developed further outside of operations within Stream 2. Stream 2 models represent cutting-edge approaches that have little or no track record; consequently, NHC forecasters do not use these models to prepare their

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John M. Lanicci

Seniors at Embry-Riddle University—many of them making their first weather forecasts—learn to see analysis and forecasting as both a scientific process and a business operation. For the last five years, a business process model has been used as a central organizing construct for the senior-level Forecasting Techniques (WX 427) course at Embry-Riddle Aeronautical University's Daytona Beach, Florida campus. The Applied Meteorology Program has been granting undergraduate degrees since 2001, so it

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Brett Roberts, Israel L. Jirak, Adam J. Clark, Steven J. Weiss, and John S. Kain

and Jirak 2014 ). Given the correspondence between supercells and observed severe weather, postprocessing techniques that use UH as their sole input have even demonstrated considerable value in highlighting the threat for severe convective hazards (e.g., Sobash et al. 2011 , 2016b ). Although the application of UH to tornado forecasting has received the most attention among these hazards (e.g., Clark et al. 2012b ; Gallo et al. 2016 ), it has also been applied successfully to operational

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Christopher C. Hennon, Kenneth R. Knapp, Carl J. Schreck III, Scott E. Stevens, James P. Kossin, Peter W. Thorne, Paula A. Hennon, Michael C. Kruk, Jared Rennie, Jean-Maurice Gadéa, Maximilian Striegl, and Ian Carley

. In general, the technique involves the interpretation of an IR image of a TC and the application of a number of constraints and set procedures. Dvorak has been used consistently at all global TC forecast agencies for at least the last 20 years, and validation studies (e.g., Gaby et al. 1980 ; Knaff et al. 2010 ) have shown that average differences between Dvorak intensity estimates and aircraft reconnaissance-based best-track data are quite low, ranging from 1.5 to 9 knots (kt; 1 kt = 0.51 m s

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Gary A. Wick, Jason P. Dunion, Peter G. Black, John R. Walker, Ryan D. Torn, Andrew C. Kren, Altug Aksoy, Hui Christophersen, Lidia Cucurull, Brittany Dahl, Jason M. English, Kate Friedman, Tanya R. Peevey, Kathryn Sellwood, Jason A. Sippel, Vijay Tallapragada, James Taylor, Hongli Wang, Robbie E. Hood, and Philip Hall

environmental conditions and, thus, where it might be advantageous to deploy additional observations. For the TC missions, a real-time technique for targeting GH dropsonde observations in the TC environment was developed at the University at Albany, State University of New York. This TC targeting algorithm, employing an ensemble-based sensitivity algorithm, identifies regions where high model forecast uncertainty (e.g., track or intensity) and a high sensitivity to assimilating additional observations (e

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Steven J. Goodman, James Gurka, Mark DeMaria, Timothy J. Schmit, Anthony Mostek, Gary Jedlovec, Chris Siewert, Wayne Feltz, Jordan Gerth, Renate Brummer, Steven Miller, Bonnie Reed, and Richard R. Reynolds

the transition from research to operations with the principal emphasis on NOAA's operational forecast office environment. This focus is accomplished by utilizing existing capabilities to simulate GOES-R products and techniques, which are then demonstrated and evaluated at NWS WFOs, NCEP, and NOAA test beds. Those users provide valuable feedback on the use of decision aids, training, and products to the development teams who make up the GOES-R Algorithm Working Group (AWG). The AWG manages and

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Christopher W. Landsea and John P. Cangialosi

Hurricane Center’s (NHC) 3-day forecast track error of the tropical cyclone’s center 1 averaged about 300 n mi (1 n mi = 1.852 km) in 1990 compared with just 100 n mi in 2016 ( Fig. 1 ; Cangialosi and Franklin 2017 ). Likewise, the 3-day forecast track error in the eastern North Pacific (east of 140°W) dropped from 225 n mi in 1990 down to 75 n mi in 2016 ( Fig. 1 ). Such changes are most assuredly due to increasingly realistic and detailed global modeling, advanced data assimilation techniques

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K. M. Lambrecht, B. J. Hatchett, L. C. Walsh, M. Collins, and Z. Tolby

given NWS forecasters an opportunity to try new communication techniques and receive rapid feedback on the potential effectiveness of new strategies. Public followers frequently post comments in response; these posts often contain insights into the values, opinions, and beliefs that reflect their attitudes toward science and forecasting uncertainty. Previous studies of public attitudes toward weather forecasts have treated uncertainty as technical uncertainty—for example, probability and likelihood

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Robin L. Tanamachi, Daniel T. Dawson II, and Loran Carleton Parker

) was designed to fulfill the following objectives for students: L1) To learn current severe weather forecasting and observation techniques L2) To have an authentic atmospheric science field work experience, using research-grade observing instruments, and opportunities to continue to work with collected data if they chose to do so L3) To expose students to various career paths in meteorology, including paths students may not have been aware of prior to taking the course, mainly through interactions

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