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Alan R. Moller

This paper describes improved methods of training volunteer tornado spotters in the National Weather Service's Skywarn program. The updated training program emphasizes the most likely tornado spawning area within a thunderstorm complex and also the types of clouds and weather phenomena that precede and accompany tornadoes. Diagrams and photographs illustrate the methods the author uses in training spotters. Finally, the early and accurate spotters' assessment of a developing tornado system and the ensuing successful NWS warning are discussed.

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Alan R. Moller

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Charles A. Doswell III, Alan R. Moller, and Harold E. Brooks

Abstract

The history of storm spotting and public awareness of the tornado threat is reviewed. It is shown that a downward trend in fatalities apparently began after the famous “Tri-State” tornado of 1925. Storm spotting’s history begins in World War II as an effort to protect the nation’s military installations, but became a public service with the resumption of public tornado forecasting, pioneered in 1948 by the Air Force’s Fawbush and Miller and begun in the public sector in 1952. The current spotter program, known generally as SKYWARN, is a civilian-based volunteer organization. Responsibility for spotter training has rested with the national forecasting services (originally, the Weather Bureau and now the National Weather Service). That training has evolved with (a) the proliferation of widespread film and (recently) video footage of severe storms; (b) growth in the scientific knowledge about tornadoes and tornadic storms, as well as a better understanding of how tornadoes produce damage; and (c) the inception and growth of scientific and hobbyist storm chasing.

The concept of an integrated warning system is presented in detail, and considered in light of past and present accomplishments and what needs to be done in the future to maintain the downward trend in fatalities. As the integrated warning system has evolved over its history, it has become clear that volunteer spotters and the public forecasting services need to be closely tied. Further, public information dissemination is a major factor in an integrated warning service; warnings and forecasts that do not reach the users and produce appropriate responses are not very valuable, even if they are accurate and timely. The history of the integration has been somewhat checkered, but compelling evidence of the overall efficacy of the watch–warning program can be found in the maintenance of the downward trend in annual fatalities that began in 1925.

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Alan R. Moller, Charles A. Doswell III, Michael P. Foster, and Gary R. Woodall

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Supercell thunderstorm forecasting and detection is discussed, in light of the disastrous weather events that often accompany supercells. The emphasis is placed on using a scientific approach to evaluate supercell potential and to recognize their presence rather than the more empirical methodologies (e.g., “rules of thumb”) that have been used in the past. Operational forecasters in the National Weather Service (NWS) can employ conceptual models of the supercell, and of the meteorological environments that produce supercells, to make operational decisions scientifically.

The presence of a mesocyclone is common to all supercells, but operational recognition of supercells is clouded by the various radar and visual characteristics they exhibit. The notion of a supercell spectrum is introduced in an effort to guide improved operational detection of supercells. An important part of recognition is the anticipation of what potential exists for supercells in the prestorm environment. Current scientific understanding suggests that cyclonic updraft rotation originates from streamwise vorticity (in the storm's reference frame) within its environment. A discussion of how storm-relative helicity can be used to evaluate supercell potential is given. An actual supercell event is employed to illustrate the usefulness of conceptual model visualization when issuing statements and warnings for supercell storms. Finally, supercell detection strategies using the advanced datasets from the modernized and restructured NWS are described.

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