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Amy McGovern, Kimberly L. Elmore, David John Gagne II, Sue Ellen Haupt, Christopher D. Karstens, Ryan Lagerquist, Travis Smith, and John K. Williams

and trained in multiple layers, ANNs can represent any nonlinear function. They also provide the foundation for deep learning methods. ANNs have been used in a wide variety of meteorology applications since the late 1980s ( Key et al. 1989 ), including cloud classification ( Bankert 1994 ), tornado prediction and detection ( Marzban and Stumpf 1996 ; Lakshmanan et al. 2005 ), damaging winds ( Marzban and Stumpf 1998 ), hail size ( Marzban and Witt 2001 ; Manzato 2013 ), precipitation

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Amy McGovern, Andrea Balfour, Marissa Beene, and David Harrison

games as an educational tool provides opportunities for deeper learning . [Available online at .] Martínez-Arocho , A. G. , P. S. Buffum , and K. E. Boyer , 2014 : Developing a game-based learning curriculum for “big data” in middle school . Proc. 45th ACM Tech. Symp. on Computer Science Education , Atlanta, GA , Assoc. Comput. Mach. , 712 , doi: 10.1145/2538862.2544296 . McClarty , K. L. , A. Orr , P. M

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Gregory R. Herman and Russ S. Schumacher

1. Introduction Machine learning algorithms have demonstrated considerable utility in many scientific disciplines, including computer vision (e.g., Rosten and Drummond 2006 ), natural language processing (e.g., Collobert et al. 2011 ), and bioinformatics (e.g., Larrañaga et al. 2006 ). Machine learning has also been used with considerable success in a wide range of future prediction scenarios, from financial market analysis (e.g., Cao and Tay 2003 ) to election forecasting (e

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Filipe Aires, Francis Marquisseau, Catherine Prigent, and Geneviève Sèze

.8, 31.4, and 89 GHz. It is a cross-track scanning radiometer, with ±48.3° from nadir with a total of 30 earth fields of view of 3.3° per scan line, providing a nominal spatial resolution of 48 km at nadir. The swath is approximately 2000 km and the instrument realizes one scan in 8 s. The AMSU-B microwave radiometer is designed to measure the atmospheric water vapor profile, with three channels in the H 2 O line at 183.31 GHz plus two window channels at 89 and 150 GHz that enable deeper penetration

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Gary S. E. Lagerloef

T-S relations, but at therisk of introducing artificial variations at the subdivision boundaries. Second, the method should remainobjective. Third, the vertical distribution of parametersshould be taken into account. An examination of theGulf of Alaska T-S distributions (Fig. 2a) reveals thata temperature of, say, 4-C at a shallow depth is morelikely to coincide with a lower salinity, while the sametemperature at a deeper level will coincide with a highersalinity. It should also be noted that

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Junho Yang, Mikyoung Jun, Courtney Schumacher, and R. Saravanan

. , 1987 : Dividing the indivisible: Using simple symmetry to partition variance explained. Proc. Second International Tampere Conf. in Statistics , Tampere, Finland, Department of Mathematical Sciences, University of Tampere, 245–260. Rasp , S. , M. S. Pritchard , and P. Gentine , 2018 : Deep learning to represent sub-grid processes in climate models . Proc. Natl. Acad. Sci. USA , 115 , 9684 – 9689 , . 10.1073/pnas.1810286115 Rienecker , M. M

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Montgomery L. Flora, Corey K. Potvin, Patrick S. Skinner, Shawn Handler, and Amy McGovern

, ProbSevere v2.0, the system can now produce probabilistic guidance for separate severe weather hazards ( Cintineo et al. 2020 ). Using a convolutional neural network (CNN; LeCun et al. 1990 ), a deep learning technique, Lagerquist et al. (2020) produced a next-hour tornado prediction system with skill comparable to the ProbSevere system. In an idealized framework, Steinkruger et al. (2020) explored using ML methods to produce automated tornado warning guidance and found promising results. Random

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Amy McGovern, Christopher D. Karstens, Travis Smith, and Ryan Lagerquist

. (1982) demonstrate that strong low-level shear is needed to create long-lived storms. Rotunno et al. (1988) demonstrate that long-lived squall lines are dependent on the interaction of low-level shear and the surface cold pool. Weisman and Klemp (1982 , 1986) demonstrate that wind shear and buoyancy are critical to both storm mode and longevity. Houston and Wilhelmson (2011) numerically study the issue of storm longevity in a low-shear environment and demonstrate that a deep cold pool is

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John R. Mecikalski, Thea N. Sandmæl, Elisa M. Murillo, Cameron R. Homeyer, Kristopher M. Bedka, Jason M. Apke, and Chris P. Jewett

-to-be-severe) deep convection ( Cintineo et al. 2014 , 2020 ). Present state-of-the-art methods that integrate a combination of weather datasets rely on raw and derived geostationary satellite parameters, gridded radar observations and derived products [e.g., the Multi-Radar Multi-Sensor (MRMS) product suite; Zhang et al. 2016 ], and NWP model fields. With respect to severe weather nowcasting (0–1 h forecasting), Probability of Severe Convection (ProbSevere; Cintineo et al. 2014 , 2018 , 2020 ), the

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Allison Engblom, Kristin Timm, Raphael Mazzone, David Perkins, Teresa Myers, and Edward Maibach

study begins to address this research need by qualitatively examining Virginia local news viewers’ interest in learning about climate change from weathercasters, their understanding of climate change messages in on-air examples, and their reactions to on-air climate change content in a television weather forecast. 2. Literature review a. The perception of climate change as a distant threat When asked what comes to mind when they think of climate change (i.e., top-of-mind associations), Americans and

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