2.1 Calibrated Probabilistic Forecasts of Aviation Hazards Using Multiple Global Ensembles

Monday, 8 January 2018: 10:30 AM
Room 16AB (ACC) (Austin, Texas)
Ken Stone, NCAR, Boulder, CO; and J. O. Pinto, M. Steiner, M. Strahan, R. Bass, and C. P. Kalb

Transoceanic flight planning in the strategic timeframe (~ 24 – 36 hours) involves the acquisition and interpretation of forecasts of aviation hazards that might be encountered along a given flight path. One key objective of ICAO is the development of globally harmonized products for common situational awareness that provide probabilistic predictions of aviation hazards (turbulence and convection). Prediction of these important atmospheric features is highly uncertain due to poor representation of physical processes in the models, inadequate resolution of global models, uncertainty in initial conditions, and limited number of ensemble members that can be run by the operational numerical weather prediction centers. In this study, we examine methods for optimally combining forecast probabilities of convection from global operational ensemble models. The aim is to provide a methodology to generate calibrated gridded products in support of the WAFCs product generation and ultimately serve as inputs for automated Decision Support Tools (DSTs).

Detailed evaluations comparing global forecast data with satellite-derived observations (e.g., CMORPH) of rainfall in the tropics reveal that despite having dissimilar Probability Density Functions (PDFs), combining calibrated probabilities obtained from multiple centers can produce more reliable forecasts than those obtained from any single center. In addition, in certain areas (e.g. Caribbean), resolution and reliability are shown to improve as calibrated probabilities from an increasing number of global models are combined. Key properties of the combined probabilistic forecast (reliability, resolution and sharpness) are assessed regionally with the goal of finding the optimal method for achieving high reliability while maintaining the resolution and sharpness of these forecasts.

Disclaimer: This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA.

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