Nathan Platt

User-Oriented Two-Dimensional Measure of Effectiveness for the Evaluation of Transport and Dispersion Models

Abstract A two-dimensional measure of effectiveness for comparing hazardous material transport and dispersion model predictions and field observations has been developed. This measure is used for comparing predictions and observations paired in space and time, and the components of this measure—overprediction, or false-positive fraction, and underprediction, or false-negative fraction—can illuminate strengths and weaknesses of a model in ways that many one-dimensional measures cannot. Comparisons of predictions of short-range field observations are used to illustrate features of this measure of effectiveness, including its computation based on dosages or based on a dosage threshold of interest. With this user-oriented measure of effectiveness, statistically significant resolution of transport and dispersion model performance differences as a function of downwind range and meteorological stability category grouping, as well as between different models, is described. Evaluation of probabilistic prediction o...

THE INTERMITTENT SOLAR CYCLE

Abstract A prominent feature of the solar cycle is the rise and fall of the number of sunspots on the surface with a timescale of approximately eleven years. The mathematical description of this behavior is complicated by the interruption of the cycle for 75 years starting around 1650. Similar previous intermissions of this kind are implied by the available data. We explore the possibility of modeling such temporal variations of the sunspot number with a deterministic dynamical system of relatively low order. The system we propose manifests on/off intermittency in which the cyclic variations of the solar activity switch off almost completely for extended periods. We also offer an explanation of the variation of the fluctuating part of the sunspot number over the cycle.

Comparisons of Transport and Dispersion Model Predictions of the Joint Urban 2003 Field Experiment

Abstract For a hazardous material release in a city or densely populated area, effective mitigation requires an understanding of the transport and dispersion of these hazards in the complex urban environment. Improved characterization and understanding of urban transport and dispersion will allow for more robust modeling. The Defense Threat Reduction Agency has developed a Hazard Prediction Assessment Capability (HPAC) that includes features to address hazardous releases within an urban environment. During the summer of 2003, a series of tracer gas releases were carried out in Oklahoma City, Oklahoma, and extensive meteorological and tracer concentration measurements were collected in a field experiment known as Joint Urban 2003 (JU03). This analysis uses the observations of JU03 to evaluate “Urban HPAC.” Twenty sets of simulations, or “predictions,” using four Urban HPAC modes and five meteorological input options, were created and compared using a variety of metrics. Strong consistency was found between...

Comparisons of Transport and Dispersion Model Predictions of the Mock Urban Setting Test Field Experiment

The potential effects of a terrorist attack involving the atmospheric release of chemical, biological, radiological, nuclear, or other hazardous materials continue to be of concern to the United States. The Defense Threat Reduction Agency has developed a Hazard Prediction Assessment Capability (HPAC) that includes initial features to address hazardous releases within an urban environment. Improved characterization and understanding of urban transport and dispersion are required to allow for more robust modeling. In 2001, a scaled urban setting was created in the desert of Utah using shipping containers, and tracer gases were released. This atmospheric tracer and meteorological study is known as the Mock Urban Setting Test (MUST). This paper describes the creation of sets of HPAC predictions and comparisons with the MUST field experiment. Strong consistency between the conclusions of this study and a previously reported HPAC evaluation that relied on urban tracer observations within the downtown area of Salt Lake City was found. For example, in both cases, improved predictions were associated with the inclusion of a simple empirically based urban dispersion model within HPAC, whereas improvements associated with the inclusion of a more computationally intensive wind field module were not found. The use of meteorological observations closest to the array and well above the obstacle array—the sonic anemometer measurements 16 m above ground level—resulted in predictions with the best fit to the observed tracer concentrations. The authors speculate that including meteorological observations or vertical wind profiles above or upwind of an urban region might be a sufficient input to create reasonable HPAC hazard-area predictions.

Comparative investigation of Source Term Estimation algorithms using FUSION field trial 2007 data: linear regression analysis

Given a warning based on detections at a few sensors, it should be useful to rapidly provide an estimate of the location, time of release and amount of material released. Such information could lead to refined predictions of the hazardous area and support follow-on actions to investigate the cause and nature of the hazardous release. In September 2007, a short-range test designed to collect data to support development of prototype Source Term Estimation (STE) algorithms was conducted. A total of eight different STE algorithm developers participated in this exercise and submitted fourteen sets of full and partial predictions. Linear regression analysis considered several variables that might influence results including the number of sensors, the release type, the time of the release, meteorological inputs and the number of sources. The results of these analyses are used to ascertain trends among different sets of STE predictions and are presented here.

Assessment of HPAC urban modelling capabilities using data from the Joint Urban 2003 field experiment

An independent evaluation was conducted of four urban prediction models included in the US Defense Threat Reduction Agencys (DTRA) Hazard Prediction and Assessment Capability (HPAC) (Version 4.0). This evaluation focused on comparing HPAC predictions with data obtained during the Joint Urban 2003 (JU03) field experiment in Oklahoma City. These models were run using a variety of meteorological inputs, including the results of forecast models and meteorological observations from the JU03 experiment. A particularly significant finding was a difference in model performance for daytime vs. nighttime tracer gas releases. Consistent significant differences in performance between models were only observed for nighttime releases.

Contrasting the Use of Single-Realization versus Ensemble-Average Atmospheric Dispersion Solutions for Chemical and Biological Defense Analyses

AbstractChemical and biological (CB) defense systems require significant testing and evaluation before they are deployed for real-time use. Because it is not feasible to evaluate these systems with open-air testing alone, researchers rely on numerical models to supplement the defense-system analysis process. These numerical models traditionally describe the statistical properties of CB-agent atmospheric transport and dispersion (AT&D). While the statistical representation of AT&D is appropriate to use in some CB defense analyses, it is not appropriate to use this class of dispersion model for all such analyses. Many of these defense-system analyses require AT&D models that are capable of simulating dispersion properties with very short time-averaging periods that more closely emulate a “single realization” of a contaminant or CB agent dispersing in a turbulent atmosphere. The latter class of AT&D models is superior to the former for performing CB-system analyses when one or more of the following factors a...

The use of probabilistic plume predictions for the consequence assessment of atmospheric releases of hazardous materials

Toxic load-based toxicity models have been increasingly applied to model the effects of atmospheric releases of hazardous materials. Although the majority of atmospheric transport and dispersion models predict only a ‘mean’ plume, real-world personnel are exposed to one of many possible individual realisations of a plume, and never to a ‘mean’ plume. Hazard prediction assessment capability (HPAC) model not only predicts the ensemble-mean dosage, but also the dosage variance, making it possible to construct a fully-probabilistic plume. We compare the ‘mean plume’ and ‘probabilistic plume’ approaches to dosage-based consequence assessment using HPAC simulations of a small-scale chemical artillery attack.

Comparison of hazard area and casualty predictions of a small-scale chemical attack using various toxic load toxicity models

It has been observed that the toxic load model can better account for toxic effects from chemical exposures than Haber’s law. However, the toxic load model has been experimentally validated only for steady exposures. We compare four proposed extensions of the toxic load model to the case of time-varying exposures. We conclude that the choice of the toxic load model can be important in consequence assessment studies that use realistic time-varying toxic exposures.

Effects of meteorological data thresholding on the quality of urban HPAC predictions of the Joint Urban 2003 field trials

Comparisons of field trial observations with predictions created by the US Defense Threat Reduction Agencys Hazard Prediction and Assessment Capability (HPAC) represent an ongoing effort. Intuitively, one might prefer to include meteorological inputs as close to the release location as possible. During Joint Urban 2003, SODARs measured vertical wind profiles?upwind, within the city centre near the releases, and downwind of Oklahoma City. Low altitude SODAR measurements fell within the urban canopy, while the upper altitude measurements were outside the canopy. In this paper, we demonstrate how the mix of lower altitude and upper altitude wind measurements affects HPAC predictions.