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urban environment on the underlying population to aid planning, emergency response, and recovery efforts. Especially desired are estimates of where and when relatively low level human-effects thresholds are exceeded (i.e., hazard regions). Models that predict the transport and dispersion of hazardous materials in urban settings are needed to develop doctrine, plan counterproliferation operations, determine and characterize the source of the hazardous release based on limited observations, develop
urban environment on the underlying population to aid planning, emergency response, and recovery efforts. Especially desired are estimates of where and when relatively low level human-effects thresholds are exceeded (i.e., hazard regions). Models that predict the transport and dispersion of hazardous materials in urban settings are needed to develop doctrine, plan counterproliferation operations, determine and characterize the source of the hazardous release based on limited observations, develop
profiles in 100-m increments (gates) through several kilometers AGL. Figure 2 shows the relative locations of the meteorological instruments that were outside of the array and used in this study—SAMS, PWIDS, tethersonde, sodar, and radar profiler. b. Brief description of HPAC urban configurations DTRA’s HPAC is composed of a suite of software modules that can generate source terms for hazardous releases, retrieve and prepare meteorological information for use in a prediction, model the transport and
profiles in 100-m increments (gates) through several kilometers AGL. Figure 2 shows the relative locations of the meteorological instruments that were outside of the array and used in this study—SAMS, PWIDS, tethersonde, sodar, and radar profiler. b. Brief description of HPAC urban configurations DTRA’s HPAC is composed of a suite of software modules that can generate source terms for hazardous releases, retrieve and prepare meteorological information for use in a prediction, model the transport and
model COAMPS forecasts were generated for each DP26 trial using the grid configuration shown in Fig. 2 . Horizontal grid spacings were 27, 9, 3, and 1 km on each of the one-way nested telescoping grids. Sixty vertical levels were employed, with the lowest level at 10 m above ground level. To resolve the boundary layer, 15 of the vertical levels resided in the lowest 1500 m of the atmosphere. Each forecast was integrated to 18 h using the full COAMPS nonhydrostatic physics. The gas releases
model COAMPS forecasts were generated for each DP26 trial using the grid configuration shown in Fig. 2 . Horizontal grid spacings were 27, 9, 3, and 1 km on each of the one-way nested telescoping grids. Sixty vertical levels were employed, with the lowest level at 10 m above ground level. To resolve the boundary layer, 15 of the vertical levels resided in the lowest 1500 m of the atmosphere. Each forecast was integrated to 18 h using the full COAMPS nonhydrostatic physics. The gas releases
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.
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.
meteorologists who issue warnings (SIGMETs, for significant meteorological information) and by personnel at air traffic control facilities and airline operation centers. Traditionally, transport and dispersion models have been evaluated near ground level using controlled tracer releases by comparing field-measured concentration areas with model-calculated areas using archived analysis meteorology (e.g., van Dop et al. 1998 ; D’Amours 1998 ). A compilation of such tracer release information is available on
meteorologists who issue warnings (SIGMETs, for significant meteorological information) and by personnel at air traffic control facilities and airline operation centers. Traditionally, transport and dispersion models have been evaluated near ground level using controlled tracer releases by comparing field-measured concentration areas with model-calculated areas using archived analysis meteorology (e.g., van Dop et al. 1998 ; D’Amours 1998 ). A compilation of such tracer release information is available on
1. Introduction A series of urban tracer-release studies in the United States in the early 2000s resulted in detailed knowledge of dispersion patterns in Oklahoma City, Oklahoma ( Allwine et al. 2002 ); Salt Lake City, Utah ( Allwine and Flaherty 2006a ); and New York City (NYC), New York ( Allwine and Flaherty 2006b , 2007 ). These large field and modeling studies illuminated the complicated pathways of horizontal and vertical transport in urban environments in summertime and have led to
1. Introduction A series of urban tracer-release studies in the United States in the early 2000s resulted in detailed knowledge of dispersion patterns in Oklahoma City, Oklahoma ( Allwine et al. 2002 ); Salt Lake City, Utah ( Allwine and Flaherty 2006a ); and New York City (NYC), New York ( Allwine and Flaherty 2006b , 2007 ). These large field and modeling studies illuminated the complicated pathways of horizontal and vertical transport in urban environments in summertime and have led to
characterization tool in the context of an operational dispersion model and with real data. Such a coupled model could be useful in source characterization for hazardous-release events for which both monitored contaminant and meteorological data are available. The primary upgrade from the HYA coupled model is the replacement of the Gaussian plume equation with the much more sophisticated Second-Order Closure Integrated Puff (SCIPUFF) dispersion model ( Sykes et al. 1998 ). The impact of upgrading the coupled
characterization tool in the context of an operational dispersion model and with real data. Such a coupled model could be useful in source characterization for hazardous-release events for which both monitored contaminant and meteorological data are available. The primary upgrade from the HYA coupled model is the replacement of the Gaussian plume equation with the much more sophisticated Second-Order Closure Integrated Puff (SCIPUFF) dispersion model ( Sykes et al. 1998 ). The impact of upgrading the coupled
the experiment itself. To address this deficiency, scientists and engineers conducting this type of work have traditionally utilized two classes of AT&D models to supplement the data collected in field experiments like FFT07. The first class includes models that describe the statistical representation of a contaminant release over many possible AT&D realizations. Models of this type acknowledge the apparent stochasticity of atmospheric turbulence and, via Reynolds averaging, calculate ensemble
the experiment itself. To address this deficiency, scientists and engineers conducting this type of work have traditionally utilized two classes of AT&D models to supplement the data collected in field experiments like FFT07. The first class includes models that describe the statistical representation of a contaminant release over many possible AT&D realizations. Models of this type acknowledge the apparent stochasticity of atmospheric turbulence and, via Reynolds averaging, calculate ensemble
particulates that are released near the ground. It utilizes a statewide mesoscale automated weather station network, the Oklahoma Mesonet ( Elliott et al. 1994 ; Brock et al. 1995 ), for current weather conditions and 60-h gridded Nested Grid Model (NGM) model output statistics (MOS) forecasts ( Dallavalle et al. 1992 ) for future conditions. The ODM generates both graphical and text output that depicts current and future conditions for both near-surface atmospheric dispersion (dilution of plume) and
particulates that are released near the ground. It utilizes a statewide mesoscale automated weather station network, the Oklahoma Mesonet ( Elliott et al. 1994 ; Brock et al. 1995 ), for current weather conditions and 60-h gridded Nested Grid Model (NGM) model output statistics (MOS) forecasts ( Dallavalle et al. 1992 ) for future conditions. The ODM generates both graphical and text output that depicts current and future conditions for both near-surface atmospheric dispersion (dilution of plume) and
1. Introduction Advancing the understanding of dispersion in urban environments is a matter of both practical and scientific importance. The ability to accurately predict the dispersion of a released agent in a city is crucial for saving lives in the event of a terrorist attack or accidental release or, to a lesser extent, for warning people of significant air pollution episodes. However, accurate modeling and simulation of dispersion in these environments has been a great challenge because of
1. Introduction Advancing the understanding of dispersion in urban environments is a matter of both practical and scientific importance. The ability to accurately predict the dispersion of a released agent in a city is crucial for saving lives in the event of a terrorist attack or accidental release or, to a lesser extent, for warning people of significant air pollution episodes. However, accurate modeling and simulation of dispersion in these environments has been a great challenge because of
