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Abdul Jabbar Abdullah

Solitary waves have been observed in shallow water. In the present paper some evidence is presented for the existence of similar phenomena in the atmosphere. A possible mechanism for the formation of atmospheric solitary waves is described, and a case study is discussed in support of this mechanism. Some speculations are made about some possible effects of these disturbances on the local weather.

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L. Cavaleri, B. Fox-Kemper, and M. Hemer

upper boundary condition for an ocean model is not restoring or having fixed fluxes—it is a full atmospheric model. Extending the range of interaction has benefited both communities. In the 1980s, wave modelers were simply users of meteorological output products—in practice, surface wind fields. However, it was quickly realized that waves imply a feedback to the atmosphere, capable of directly affecting the evolution of weather systems. This led, at least in some institutions, to two-way coupling of

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David M. Tratt, John A. Hackwell, Bonnie L. Valant-Spaight, Richard L. Walterscheid, Lynette J. Gelinas, James H. Hecht, Charles M. Swenson, Caleb P. Lampen, M. Joan Alexander, Lars Hoffmann, David S. Nolan, Steven D. Miller, Jeffrey L. Hall, Robert Atlas, Frank D. Marks Jr., and Philip T. Partain

. 2009 ). GWs are waves in a fluid medium where the restoring force is buoyancy; they are the ubiquitous consequence of powerful disturbances in the atmosphere and are caused by thunderstorms, TCs, and other extreme events. The relation between GWs and storms is illustrated by the snapshot in Fig. 1 of waves radiated by cyclonic storm systems as observed in a carbon dioxide (CO 2 ) spectral band by the Atmospheric Infrared Sounder (AIRS). The retrieved brightness temperature (BT) excursions of the

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Gregory Dusek, Christopher DiVeglio, Louis Licate, Lorraine Heilman, Katie Kirk, Christopher Paternostro, and Ashley Miller

about 2 m in height that crashed into a jetty, knocking several people into the water and resulting in multiple injuries ( Bailey et al. 2014 ). There were other eyewitness reports along the U.S. East Coast of a large wave with impacts similar to what might be expected from a tsunami wave. It quickly became apparent that this large wave was a meteotsunami, or an atmospherically induced ocean wave in the tsunami-frequency band ( Bailey et al. 2014 ; Wertman et al. 2014 ). An intense squall line

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Roland A. Madden

waves ( Wallace and Kousky 1968 ) in the stratosphere that were predicted by Matsuno’s theory. In addition, they showed how spectral analysis could be used effectively to detect and to describe these and other synoptic-scale tropospheric waves (e.g., Yanai et al. 1968 ; Wallace and Chang 1969 ; Wallace 1971 ). With this as a background, members of the Synoptic Meteorology Group at the National Center for Atmospheric Research (NCAR) began work with Line Islands Experiment (LIE) data. The LIE

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Qing Wang, Denny P. Alappattu, Stephanie Billingsley, Byron Blomquist, Robert J. Burkholder, Adam J. Christman, Edward D. Creegan, Tony de Paolo, Daniel P. Eleuterio, Harindra Joseph S. Fernando, Kyle B. Franklin, Andrey A. Grachev, Tracy Haack, Thomas R. Hanley, Christopher M. Hocut, Teddy R. Holt, Kate Horgan, Haflidi H. Jonsson, Robert A. Hale, John A. Kalogiros, Djamal Khelif, Laura S. Leo, Richard J. Lind, Iossif Lozovatsky, Jesus Planella-Morato, Swagato Mukherjee, Wendell A. Nuss, Jonathan Pozderac, L. Ted Rogers, Ivan Savelyev, Dana K. Savidge, R. Kipp Shearman, Lian Shen, Eric Terrill, A. Marcela Ulate, Qi Wang, R. Travis Wendt, Russell Wiss, Roy K. Woods, Luyao Xu, Ryan T. Yamaguchi, and Caglar Yardim

The objective of CASPER is to improve our capability to characterize the propagation of radio frequency (RF) signals through the marine atmosphere with coordinated efforts in data collection, data analyses, and modeling of the air–sea interaction processes, refractive environment, and RF propagation. ATMOSPHERIC VERTICAL STRUCTURE AND EM DUCTING. Propagation of electromagnetic (EM) waves from radar or communication devices can be significantly impacted by atmospheric refractive conditions

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D. R. Jackson, A. Gadian, N. P. Hindley, L. Hoffmann, J. Hughes, J. King, T. Moffat-Griffin, A. C. Moss, A. N. Ross, S. B. Vosper, C. J. Wright, and N. J. Mitchell

perturbations T ʹ are found by removing the background temperature state via a fourth-order polynomial fit method as described in Wright et al. (2017) . The 3D S-transform then allows us to measure wave amplitude T ʹ and zonal, meridional, and vertical wavenumbers k , l , and m ( Wright et al. 2017 ). Then, using the relation from Ern et al. (2004) , the momentum flux in the zonal and meridional directions ( M x , M y ) can be computed as where ρ is the background atmospheric density, g is

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Thomas C. Peterson, Richard R. Heim Jr., Robert Hirsch, Dale P. Kaiser, Harold Brooks, Noah S. Diffenbaugh, Randall M. Dole, Jason P. Giovannettone, Kristen Guirguis, Thomas R. Karl, Richard W. Katz, Kenneth Kunkel, Dennis Lettenmaier, Gregory J. McCabe, Christopher J. Paciorek, Karen R. Ryberg, Siegfried Schubert, Viviane B. S. Silva, Brooke C. Stewart, Aldo V. Vecchia, Gabriele Villarini, Russell S. Vose, John Walsh, Michael Wehner, David Wolock, Klaus Wolter, Connie A. Woodhouse, and Donald Wuebbles

( Fig. 1 ). However, the post-2000 portion of the minimum temperature series in Fig. ES1 (the warmest stretch in the record) does correspond with the 2000s in Fig. 1 , showing the smallest number of cold waves of any decade. Atmospheric moisture plays an important role in heat waves. The impact of heat waves on humans is exacerbated by high humidity (e.g., the deadly 1995 Chicago heat wave; Karl and Knight 1997 ). Gaffen and Ross (1998) found significant increases in apparent temperature over

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Jennifer A. MacKinnon, Zhongxiang Zhao, Caitlin B. Whalen, Amy F. Waterhouse, David S. Trossman, Oliver M. Sun, Louis C. St. Laurent, Harper L. Simmons, Kurt Polzin, Robert Pinkel, Andrew Pickering, Nancy J. Norton, Jonathan D. Nash, Ruth Musgrave, Lynne M. Merchant, Angelique V. Melet, Benjamin Mater, Sonya Legg, William G. Large, Eric Kunze, Jody M. Klymak, Markus Jochum, Steven R. Jayne, Robert W. Hallberg, Stephen M. Griffies, Steve Diggs, Gokhan Danabasoglu, Eric P. Chassignet, Maarten C. Buijsman, Frank O. Bryan, Bruce P. Briegleb, Andrew Barna, Brian K. Arbic, Joseph K. Ansong, and Matthew H. Alford

from ocean boundaries (atmosphere, ice, or the solid ocean bottom), diapycnal mixing is largely related to the breaking of internal gravity waves, which have a complex dynamical underpinning and associated geography. Consequently, in 2010, a Climate Process Team (CPT), funded by the National Science Foundation (NSF) and the National Atmospheric and Oceanic Administration (NOAA), was convened to consolidate knowledge on internal wave–driven turbulent mixing in the ocean, develop new and more

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Ibrahim Hoteit, Yasser Abualnaja, Shehzad Afzal, Boujemaa Ait-El-Fquih, Triantaphyllos Akylas, Charls Antony, Clint Dawson, Khaled Asfahani, Robert J. Brewin, Luigi Cavaleri, Ivana Cerovecki, Bruce Cornuelle, Srinivas Desamsetti, Raju Attada, Hari Dasari, Jose Sanchez-Garrido, Lily Genevier, Mohamad El Gharamti, John A. Gittings, Elamurugu Gokul, Ganesh Gopalakrishnan, Daquan Guo, Bilel Hadri, Markus Hadwiger, Mohammed Abed Hammoud, Myrl Hendershott, Mohamad Hittawe, Ashok Karumuri, Omar Knio, Armin Köhl, Samuel Kortas, George Krokos, Ravi Kunchala, Leila Issa, Issam Lakkis, Sabique Langodan, Pierre Lermusiaux, Thang Luong, Jingyi Ma, Olivier Le Maitre, Matthew Mazloff, Samah El Mohtar, Vassilis P. Papadopoulos, Trevor Platt, Larry Pratt, Naila Raboudi, Marie-Fanny Racault, Dionysios E. Raitsos, Shanas Razak, Sivareddy Sanikommu, Shubha Sathyendranath, Sarantis Sofianos, Aneesh Subramanian, Rui Sun, Edriss Titi, Habib Toye, George Triantafyllou, Kostas Tsiaras, Panagiotis Vasou, Yesubabu Viswanadhapalli, Yixin Wang, Fengchao Yao, Peng Zhan, and George Zodiatis

built by integrating models of atmospheric and oceanic circulations, surface wave, air pollution, dust, and marine biogeochemistry, and developing advanced data analytics and visualization capabilities, achieving remarkable progress in the short span of a decade. The modeling system also relies on in situ and remotely sensed observations (detailed in Table 1 ) for the purpose of validation and data assimilation and provides insights into the systematic relations between the interactions of

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