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Thomas J. Sullivan, James S. Ellis, Connee S. Foster, Kevin T. Foster, Ronald L. Baskett, John S. Nasstrom, and Walter W. Schalk III

The Atmospheric Release Advisory Capability (ARAC) at Lawrence Livermore National Laboratory is a centralized federal project for assessing atmospheric releases of hazardous materials in real time. Since ARAC began making assessments in 1974, the project has responded to over 60 domestic and international incidents. ARAC can model radiological accidents in the United States within 30 to 90 min, using its operationally robust, three-dimensional atmospheric transport and dispersion models, extensive geophysical and dose-factor databases, meteorological data acquisition systems, and experienced staff. Although it was originally conceived and developed as an emergency response and assessment service for providing dose-assessment calculations after nuclear accidents, it has proven to be an extremely adaptable system, capable of being modified to respond also to nonradiological hazardous releases. In 1991, ARAC responded to three major events: the oil fires in Kuwait, the eruption of Mt. Pinatubo in the Philippines, and an herbicide spill into the upper Sacramento River in California. Modeling the atmospheric effects of these events added significantly to the range of problems that ARAC can address and demonstrated that the system can be adapted to assess and respond to concurrent, multiple, unrelated events at different locations.

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David J. Stensrud, Ming Xue, Louis J. Wicker, Kevin E. Kelleher, Michael P. Foster, Joseph T. Schaefer, Russell S. Schneider, Stanley G. Benjamin, Stephen S. Weygandt, John T. Ferree, and Jason P. Tuell

The National Oceanic and Atmospheric Administration's (NOAA's) National Weather Service (NWS) issues warnings for severe thunderstorms, tornadoes, and flash floods because these phenomena are a threat to life and property. These warnings are presently based upon either visual confirmation of the phenomena or the observational detection of proxy signatures that are largely based upon radar observations. Convective-scale weather warnings are unique in the NWS, having little reliance on direct numerical forecast guidance. Because increasing severe thunderstorm, tornado, and flash-flood warning lead times are a key NOAA strategic mission goal designed to reduce the loss of life, injury, and economic costs of these high-impact weather phenomena, a new warning paradigm is needed in which numerical model forecasts play a larger role in convective-scale warnings. This new paradigm shifts the warning process from warn on detection to warn on forecast, and it has the potential to dramatically increase warning lead times.

A warn-on-forecast system is envisioned as a probabilistic convective-scale ensemble analysis and forecast system that assimilates in-storm observations into a high-resolution convection-resolving model ensemble. The building blocks needed for such a system are presently available, and initial research results clearly illustrate the value of radar observations to the production of accurate analyses of convective weather systems and improved forecasts. Although a number of scientific and cultural challenges still need to be overcome, the potential benefits are significant. A probabilistic convective-scale warn-on-forecast system is a vision worth pursuing.

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Kevin A. Scharfenberg, Daniel J. Miller, Terry J. Schuur, Paul T. Schlatter, Scott E. Giangrande, Valery M. Melnikov, Donald W. Burgess, David L. Andra Jr., Michael P. Foster, and John M. Krause

Abstract

To test the utility and added value of polarimetric radar products in an operational environment, data from the Norman, Oklahoma (KOUN), polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) were delivered to the National Weather Service Weather Forecast Office (WFO) in Norman as part of the Joint Polarization Experiment (JPOLE). KOUN polarimetric base data and algorithms were used at the WFO during the decision-making and forecasting processes for severe convection, flash floods, and winter storms. The delivery included conventional WSR-88D radar products, base polarimetric radar variables, a polarimetric hydrometeor classification algorithm, and experimental polarimetric quantitative precipitation estimation algorithms. The JPOLE data collection, delivery, and operational demonstration are described, with examples of several forecast and warning decision-making successes. Polarimetric data aided WFO forecasters during several periods of heavy rain, numerous large-hail-producing thunderstorms, tornadic and nontornadic supercell thunderstorms, and a major winter storm. Upcoming opportunities and challenges associated with the emergence of polarimetric radar data in the operational community are also described.

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