5.3 Improving NOAA G-IV Synoptic Surveillance Targeting for Tropical Cyclones by Evaluating Aircraft Reconnaissance Observations in an OSSE Framework

Tuesday, 24 January 2017: 11:00 AM
607 (Washington State Convention Center )
Kelly Ryan, NOAA/AOML and University of Miami, Miami, FL; and L. Bucci, J. Delgado, R. Atlas, C. W. Landsea, and S. Murillo

Aircraft reconnaissance missions remain the only means of collecting direct measurements of marine atmospheric conditions affecting tropical cyclone formation and evolution. The National Hurricane Center tasks the NOAA G-IV aircraft to sample environmental conditions that may impact the development of a tropical cyclone threatening to make landfall in the United States or its territories. These aircraft data are assimilated into deterministic models and used to produce real-time analyses and forecasts for a given tropical cyclone. Existing targeting techniques aim to optimize the use of reconnaissance observations and rely on regions of highest uncertainty in the Global Ensemble Forecast System (GEFS).  Evaluating the potential impact of various trade-offs in the targeting process is valuable for determining the ideal aircraft reconnaissance flight track for a prospective mission.

AOML’s Hurricane Research Division has developed a system for performing regional Observing System Simulation Experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasts and analyses. This project focuses on improving existing targeting methods by investigating the impact of proposed aircraft reconnaissance observing system designs through various sensitivity studies. Aircraft instrument and flight level retrievals were simulated from a regional WRF ARW Nature Run (Nolan et al., 2013) spanning 13 days, covering the life cycle of a rapidly intensifying Atlantic tropical cyclone. Results from sensitivity studies provide insight into improvements for real-time operational synoptic surveillance targeting for hurricanes and tropical storms.

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