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Analysis of Weather Forecast Impacts on United States Air Force Combat Operations

Analysis of Weather Forecast Impacts on United States Air Force Combat Operations. Thesis Research Project b y Major Karen Darnell, USAF Naval Postgraduate School (NPS) kmdarnel@nps.edu Advisors: Prof Tom Murphree, NPS Col Dave Smarsh, NPS AFWA/CC Briefing 16 March 2006

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Analysis of Weather Forecast Impacts on United States Air Force Combat Operations

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  1. Analysis of Weather Forecast Impacts on United States Air Force Combat Operations Thesis Research Project by Major Karen Darnell, USAF Naval Postgraduate School (NPS) kmdarnel@nps.edu Advisors: Prof Tom Murphree, NPS Col Dave Smarsh, NPS AFWA/CC Briefing 16 March 2006 Research supported in part by funding from Office of Naval Research and Space and Naval Warfare Systems Center

  2. Motivation and Goals • CWT Challenges • AFMAN 15-129 & AFI 15-114: measure relevancy of AFW products to customers, conduct operational verification, develop process improvement metrics, and operator debriefs (face-to-face preferred) • Air Force Audit Agency Report released Sep 2005: deficiencies in customer feedback processes, no standard procedure in AFIs • Manpower not adequate to embed, high number of deployments • Goals • Adapt existing web-based, near-real time system for collecting and analyzing data • Implement and test system to assess value AFW, ACC, & PACAF • Use results to provide AFW, ACC, and PACAF advice on how to alter procedures and allocation of resources to better accomplish goals Maj Darnell NPS AFWA/CC Brief, 16 Mar 06, POC: kmdarnel@nps.edu

  3. Data and Methods • Data: • From aviators: Beale AFB (U-2), Dyess AFB (B-1), Kunsan AB (F-16), Nellis AFB (A-10), Osan AB (A-10 & F-16), Whiteman AFB (B-2) • Type: planning/execution forecasts, mission planning impacts due to forecasts, aircrew-observed weather, operational impacts of weather on mission • Timeframe: Oct 05 – Jan 06 • NPS AF aviator survey • Methods: • Paper copy and online forms from aviators (predominantly flight leads) • Data archived and analyzed in close to near-real time at NPS to calculate forecast performance and operational impacts metrics Maj Darnell NPS AFWA/CC Brief, 16 Mar 06, POC: kmdarnel@nps.edu

  4. Results 107 Missions Analyzed: 82% Successful, 7% Unsuccessful, 11% Unknown Osan AB: 40% Dyess AFB: 17% Whiteman AFB: 16% Kunsan AB: 14% Nellis AFB: 8% Beale AFB: 5% F-16: 38% A-10: 24% B-1: 17% B-2: 16% U-2: 5% http://wx.met.nps.navy.mil/metrics/airforce PWFs indicated negative weather impacts: 36% Mission plans changed due to PWFs: 21% MEFs indicated negative weather impacts: 39% Mission plans changed due to MEFs: 21% Missions that experienced negative wx impacts: 36% Mean PWFFAC: 69.2% Mean MEFFAC: 69.2% Mean PWFPOD: 65.5% Mean MEFPOD: 65.5% Mean PWFFAR: 31.2% Mean MEFFAR: 52.1% Maj Darnell NPS AFWA/CC Brief, 16 Mar 06, POC: kmdarnel@nps.edu

  5. Results Negative Mission Impacts Occurring Mission Plan Changes Positive Mission Contribution Potential Positive Mission Contribution Maj Darnell NPS AFWA/CC Brief, 16 Mar 06, POC: kmdarnel@nps.edu

  6. Recommendations for AFW • Include system in AFI 15-114 as prototype for customer feedback and metrics • Compare mission success at bases with embedded vs non-embedded wx personnel • Direct R&D, E&T funds toward surface visibility, cloud ceilings and cloud layers • Educate aviators on wx products via IRC • Adapt this system to OWSs Maj Darnell NPS AFWA/CC Brief, 16 Mar 06, POC: kmdarnel@nps.edu

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