J10.5 Enhancing Hurricane Analysis and Prediction through Advanced Assimilation of High-resolution Radar and Satellite Observations

Tuesday, 12 January 2016: 4:30 PM
Room 344 ( New Orleans Ernest N. Morial Convention Center)
Fuqing Zhang, Pennsylvania State University, University Park, PA; and M. Minamide, E. E. Clothiaux, Y. Weng, and S. Sieron

We will first summarize recent advances in the prediction of hurricane intensity and associated hazards through a newly developed convection-permitting forecast system that uses ensemble data assimilation techniques to ingest high-resolution airborne radar observations from the inner core. Averaged over all 102 applicable cases that have inner-core airborne Doppler radar observations during 2008-2012, the system reduced the day-2-to-day-4 intensity forecast errors by 25-28% compared to the corresponding National Hurricane Center's official forecasts.

We further demonstrate the potential of using the ensemble-based data assimilation system to assimilate satellite infrared radiance observations from to-be-launched GOES-R on the analysis and forecast of tropical cyclones. GOES-R will contain 10 infrared channels with 2 km x 2 km spatial resolution with images produced every 15 minutes. The assimilation of such high-resolution GOES-R satellite observations in both clear and cloudy skies is challenging but the preliminary results through the observing system simulation experiments are very encouraging for both convection-permitting hurricane analysis and prediction.

Empowered by sufficient computing resources, advances in both deterministic and probabilistic hurricane prediction will enable emergency management officials, the private sector, and the general public to make more informed decisions that minimize the losses of life and property.

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