|Acquisition Program: ||PEO Command, Control and Communications Tactical|| Objective: ||Develop approaches and methodologies for using mesoscale ensemble modeling to produce forecast probabilities of meteorological variables critical to aviation. Establish capability to calculate forecast probabilities for meteorological parameters using ensemble model forecasts for determination of weather impacts on manned and unmanned aircraft flight routes.
|| Description: ||Army aviation meteorological forecasts and associated automated decision aids and assessment tools suffer from a lack of accuracy, uncertainty and reliability due to the inherent uncertainty in weather forecasts. This problem can be substantially solved by translating high-resolution, mesoscale ensemble model output to forecast probabilities for meteorological parameters along a flight path (ensemble forecasting ia a numerical prediction method used to generate a representative sample of the possible future states of a dynamical system). These forecast probabilities can then be applied to mission planning and operations risk assessment and management to increase the likelihood of mission success.
The probabilistic forecast output can be used in weighting schemes to assess the overall aviation mission risk and/or impacts due to the weather. This meteorological impact determination for aviation missions, operations and flights will advance the capabilities of the Army’s Aviation Weather Routing Tool (AWRT), the Tri-Service Integrated Weather Effects Decision Aid (T-IWEDA), and other aviation weather support tools and applications with new probabilistic presentation capabilities to enhance decision-making and course of action options. This capability will improve aviation mission effectiveness, efficiency, safety and survivability.
Ensemble model forecast probability output is required for applications of mesoscale model probabilistic forecasts of aviation impact parameters to be used for aviation route optimization, aviation mission planning and assessment of weather-related mission effectiveness and risk. Such probabilistic forecasts will revolutionize today’s deterministic forecasts by providing confidence and risk parameters as part of the forecast products. Thus, commanders will have added and focused critical weather confidence factors to aid them in battlefield decisions impacted by adverse weather conditions.
|| ||PHASE I: Determine technical feasibility and develop approaches to producing probabilistic forecasts of specific aviation weather variables such as icing, turbulence, thunderstorms, winds, and clouds from mesoscale ensemble model output for aviation meteorology. Establish a method (or methods) of calculating ensemble model forecast probabilities for aviation meteorological parameters and apply these methods to individual parameter probabilistic predictions. Develop an initial capability to take one parameter’s adverse weather threshold probability of occurrence and translate that to an adverse weather impact display for a grid point, flight leg, and an entire flight route.
|| ||PHASE II: Implement the novel approach and methodology developed in Phase I to produce a prototype model and software that will output ensemble model forecast probabilities for aviation meteorological parameters at every grid point of the Weather Research and Forecasting (WRF) weather forecast model. Adapt these grid point parameter probabilities for up to five parameters at a grid point, along a flight leg, and along an entire flight path. Produce overall grid point, flight leg, and flight path weather impact calculations based on a combined probabilistic adverse weather impact calculation from these grid point probabilistic values. Develop and implement the capability to adjust weights of up to five parameters in a hierarchal scenario where one or two parameters are declared “more significant” than the others. Calculate and display overall adverse weather impact calculations based on such a weighting scheme and display these calculations at a grid point, along a flight leg, and along an entire flight path.
|| ||PHASE III: The ability to determine the accuracy and reliability of mesoscale ensemble model forecast output of aviation meteorological parameters through ensemble probabilistic forecasting is vital to improving and supporting military, civilian and commercial aviation operations and applications, and is a critical capability needed in the Distributed Common Ground Station - Army (DCGS-A) Weather Services and the Tactical Airspace Integration System (TAIS). Mesoscale meteorological ensemble model probabilistic forecasts for Army aviation support and applications would greatly benefit the Air Force, Navy, Marine Corps, civilian and commercial aviation communities. The utility of the aviation meteorological forecast probabilities would be used across the board to determine overall mission and flight impacts, effectiveness, and airspace management risk assessment for commercial, civilian, and military aircraft and aviation activities. Such calculations will benefit flight planning and mission execution aircraft routing decisions designed to help manned and unmanned aircraft avoid adverse weather conditions.
|| References: ||
1. Eckel, F. A., Cunningham J. G., and D. E. Hetke, 2008: Weather and the calculated risk: Exploiting forecast uncertainty for Operational Risk Management. Air & Space Power Journal, 22, 71–82.
2. Grimit, E. P., and C. F. Mass, 2007: Measuring the Ensemble Spread–Error Relationship with a Probabilistic Approach: Stochastic Ensemble Results. Monthly Weather Review, 135, 203–221.
3. Eckel, F. A. and C. F. Mass, 2005: Aspects of effective mesoscale short-range ensemble forecasting. Weather Forecasting, 20, 328-350.
|Keywords: ||Mesoscale ensemble model, probabilistic forecasts, aviation meteorology, weather impacts|