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Applying Ensemble Prediction Systems to DoD Operations. 1Lt Jeffrey Cunningham, USAF AFIT Graduate Student at the Naval Postgraduate School. E-mail Address jgcunnin@nps.navy.mil. Support AF Thesis Sponsor: Major Tony Eckel at AFWA/DNXM (AF Thesis TOPIC 39)
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Applying Ensemble Prediction Systems to DoD Operations 1Lt Jeffrey Cunningham, USAF AFIT Graduate Student at the Naval Postgraduate School E-mail Address jgcunnin@nps.navy.mil Support AF Thesis Sponsor: Major Tony Eckel at AFWA/DNXM (AF Thesis TOPIC 39) NPS Thesis Advisors: Dr. Chuck Wash & Dr. Pat Harr
Introduction - Thesis Motivation • The atmosphere has a limit of predictability. • This causes there to be uncertainty in forecasts • Traditional deterministic forecasts lack important uncertainty information (Wilks 1995; Anthes 1986; Lewis 2005). • Quantifying uncertainty may improve a weather forecast user’s ability to make better decisions according to their utility functions (Zhu et al. 2002), which could translate to better operational risk management for the Air Force. • Traditional deterministic forecasts will likely be inadequate for future advanced dynamic decision-making models that will be inherent in advanced weapon systems. • Timely and reliable automated forecasts will be needed for machine-to-machine operations
Case 3 Blue – Probabilistic System Red – Deterministic System
12 Hour Probabilistic Forecast (FL 260-330) Probability of MDT or greater Turbulence Legend Deterministic Forecast Original AR Track MDT Turbulence Alternative AR Track
Relating C and L to military forecast users C is assumed to be a fixed average cost of protecting L is a function of mission priority and risk level, with mission priority having more value than risk level.