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Christopher M. Fuhrmann, Charles E. Konrad II, Margaret M. Kovach, Jordan T. McLeod, William G. Schmitz, and P. Grady Dixon


The calendar year 2011 was an extraordinary year for tornadoes across the United States, as it marked the second highest annual number of tornadoes since 1950 and was the deadliest tornado year since 1936. Most of the fatalities in 2011 occurred in a series of outbreaks, highlighted by a particularly strong outbreak across the southeastern United States in late April and a series of outbreaks over the Great Plains and Midwest regions in late May, which included a tornado rated as a category 5 event on the enhanced Fujita scale (EF5) that devastated the town of Joplin, Missouri. While most tornado-related fatalities often occur in outbreaks, very few studies have examined the climatological characteristics of outbreaks, particularly those of varying strength. In this study a straightforward metric to assess the strength, or physical magnitude, of tornado outbreaks east of the Rocky Mountains from 1973 to 2010 is developed. This measure of outbreak strength, which integrates the intensity of tornadoes [Fujita (F)/EF-scale rating] over their distance traveled (pathlength), is more highly correlated with injuries and fatalities than other commonly used variables, such as the number of significant tornadoes, and is therefore more reflective of the potential threat of outbreaks to human life. All outbreaks are then ranked according to this metric and their climatological characteristics are examined, with comparisons made to all other tornadoes not associated with outbreaks. The results of the ranking scheme are also compared to those of previous studies, while the strongest outbreaks from 2011 are ranked among other outbreaks in the modern record, including the April 1974 Super Outbreak.

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P. G. Dixon, D. M. Brommer, B. C. Hedquist, A. J. Kalkstein, G. B. Goodrich, J. C. Walter, C. C. Dickerson IV, S. J. Penny, and R. S. Cerveny

Studies, public reports, news reports, and Web sites cite a wide range of values associated with deaths resulting from excessive heat and excessive cold. For example, in the United States, the National Climatic Data Center's Storm Data statistics of temperature-related deaths are skewed heavily toward heat-related deaths, while the National Center for Health Statistics Compressed Mortality Database indicates the reverse—4 times more people die of “excessive cold” conditions in a given year than of “excessive heat.” In this study, we address the fundamental differences in the various temperature-related mortality databases, assess their benefits and limitations, and offer suggestions as to their use. These datasets suffer from potential incompleteness of source information, long compilation times, limited quality control, and the subjective determination of a direct versus indirect cause of death. In general, these separate mortality datasets should not be combined or compared, particularly with regard to policy determination. The use of gross mortality numbers appears to be one of the best means of determining temperature-related mortality, but those data must be detrended into order to remove a persistent winter-dominant death maximum and are difficult to obtain on a regional daily basis.

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G. de Boer, C. Diehl, J. Jacob, A. Houston, S. W. Smith, P. Chilson, D. G. Schmale III, J. Intrieri, J. Pinto, J. Elston, D. Brus, O. Kemppinen, A. Clark, D. Lawrence, S. C. C. Bailey, M.P. Sama, A. Frazier, C. Crick, V. Natalie, E. Pillar-Little, P. Klein, S. Waugh, J. K. Lundquist, L. Barbieri, S. T. Kral, A. A. Jensen, C. Dixon, S. Borenstein, D. Hesselius, K. Human, P. Hall, B. Argrow, T. Thornberry, R. Wright, and J. T. Kelly
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Gijs de Boer, Constantin Diehl, Jamey Jacob, Adam Houston, Suzanne W. Smith, Phillip Chilson, David G. Schmale III, Janet Intrieri, James Pinto, Jack Elston, David Brus, Osku Kemppinen, Alex Clark, Dale Lawrence, Sean C. C. Bailey, Michael P. Sama, Amy Frazier, Christopher Crick, Victoria Natalie, Elizabeth Pillar-Little, Petra Klein, Sean Waugh, Julie K. Lundquist, Lindsay Barbieri, Stephan T. Kral, Anders A. Jensen, Cory Dixon, Steven Borenstein, Daniel Hesselius, Kathleen Human, Philip Hall, Brian Argrow, Troy Thornberry, Randy Wright, and Jason T. Kelly


Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research Using Remotely-Piloted Aircraft (ISARRA) has been developed and has convened annual meetings and “flight weeks.” The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE), involved a 1-week deployment to Colorado’s San Luis Valley. Between 14 and 20 July 2018 over 100 students, scientists, engineers, pilots, and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated “Community Day” which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1,300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques, and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.

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Keith A. Browning, Alan M. Blyth, Peter A. Clark, Ulrich Corsmeier, Cyril J. Morcrette, Judith L. Agnew, Sue P. Ballard, Dave Bamber, Christian Barthlott, Lindsay J. Bennett, Karl M. Beswick, Mark Bitter, Karen E. Bozier, Barbara J. Brooks, Chris G. Collier, Fay Davies, Bernhard Deny, Mark A. Dixon, Thomas Feuerle, Richard M. Forbes, Catherine Gaffard, Malcolm D. Gray, Rolf Hankers, Tim J. Hewison, Norbert Kalthoff, Samiro Khodayar, Martin Kohler, Christoph Kottmeier, Stephan Kraut, Michael Kunz, Darcy N. Ladd, Humphrey W. Lean, Jürgen Lenfant, Zhihong Li, John Marsham, James McGregor, Stephan D. Mobbs, John Nicol, Emily Norton, Douglas J. Parker, Felicity Perry, Markus Ramatschi, Hugo M. A. Ricketts, Nigel M. Roberts, Andrew Russell, Helmut Schulz, Elizabeth C. Slack, Geraint Vaughan, Joe Waight, David P. Wareing, Robert J. Watson, Ann R. Webb, and Andreas Wieser

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model.

A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP.

This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

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