High Resolution Micro-meteorological Tools for Global War on Terrorism (GWOT) Contaminant Transport and Dispersal Predictions

Next Century Corporation and the University of Washington’s Department of Atmospheric Sciences propose development of the Micro-Meteorological Modeling (M3) system with the goal of rapidly performing high-resolution atmospheric dispersion modeling, ideally down to the microscale level, with a high degree of accuracy and confidence. Our M3 graphical user interface will provide the user with a highly intuitive display of the often complex results of these dispersion models, including risk assessment and confidence information. The M3 dispersion modeling capabilities will exploit the probabilistic forecast output of the Joint Ensemble Forecast System (JEFS). Our key innovations for designing and building the M3 solution proposed herein are primarily focused on: (1) innovative visualization, portrayal and decision support paradigms, (2) advanced algorithms and techniques for high resolution atmospheric modeling, and (3) a modular, component-based, open architecture for interoperability and extensibility. Our Phase I Base Period activities will focus on (a) rapid prototyping of user interface paradigms and visualization techniques and (b) preliminary algorithm development, refinement and selection. In addition to a Final Report, our Phase 1 deliverables will include a proof-of-concept prototype.BENEFITS: Our M3 solution’s innovative and effective techniques for employing probabilistic forecasts to help improve the accuracy and precision of dispersion model output, coupled with our intuitive visualization paradigms for displaying model output based on risk and uncertainty, are expected to elicit strong interest from a wide range of homeland security, DoD and commercial users. In the DoD market, for example, the criticality of accurate weather forecasts to the success of U.S. military operations is driving a number of significant DoD-funded initiatives that are attempting to provide our military forces with an ever-improved rapid and accurate assessment of anticipated weather conditions. In addition to the leading edge research and development being performed by the team at the University of Washington’s Department of Atmospheric Sciences, the Center for Geosciences/Atmospheric Research at Colorado State University, Johns Hopkins University’s Applied Physics Lab (APL) and the University of Alaska’s Geophysical Institute are just a few additional examples of research institutions that are under multi-million dollar contracts, often jointly sponsored by multiple branches of the military, to address known challenges and issues in this domain. Similarly, major development efforts such as the Joint Ensemble Forecast System (JEFS) are being heavily funded due to the expectation that such tools will yield tremendous benefits for their users. The value of such decision aids to DoD users is of equal importance to users in the commercial marketplace. For agricultural and energy commodity traders, food processing businesses, utilities and transportation companies, individual success and competitive advantage is highly dependent upon rapid access to accurate weather forecast and dispersion model information. Similarly, civilian agencies such as NOAA could benefit from a probabilistic forecast risk-based decision aid for determining when, for example, to evacuate populated areas due to the probability of contaminant dispersion. Probability forecasts are also expected to have significant economic benefits for the nation. Since a substantial portion of the economy is weather sensitive, a new economic sector of weather risk management has emerged. This management industry provides a “hedging tool,” allowing companies to even out their weather sensitive costs. Better management by these companies, through effective tools such as probability forecasts, therefore benefits the general public in the form of lower cost for commodities, such as power. The energy industry already spends more than $50 million per year on private forecasts or hiring their own internal meteorologists. For the travel industry, the M3 tool could potentially aid in avoiding poor or unsafe travel conditions. Risk-based dispersion model analysis would be a vital asset for managing travel risk to determine the best route or time window of travel. The leisure, commercial trucking, and private air travel industry spends $5-10MM per year for basic weather information. A decision support system that combines travel risk tolerance with uncertainty in weather forecasts and dispersion modeling could itself be a several million dollar per year market. We anticipate three M3-related revenue streams; namely, software licenses, software maintenance services, and custom application development. Although pricing details for the product remain to-be-determined, the significant size of the market gives us substantial confidence that further investment in development of the M3 product is warranted and likely to yield a high return.