J10.3 The Hurricane Forecast Improvement Project: Progress in Hurricane Prediction Since Hurricane Katrina

Tuesday, 12 January 2016: 4:00 PM
Room 344 ( New Orleans Ernest N. Morial Convention Center)
Frank D. Marks Jr., NOAA/AOML, Miami, FL; and F. Toepfer, E. Rappaport, V. Tallapragada, S. Gopalakrishnan, and R. L. Gall

The significant, harmful impacts of hurricanes like Katrina can be mitigated through accurate and timely warnings delivered to the public. In order to provide this information, NOAA fosters a robust research enterprise and real-time capability to model and observe environmental conditions associated with the development and impact of hurricanes and to provide advanced warning products to the public. Partially in response to the significant impacts caused by Katrina NOAA initiated a concerted effort in 2009 to accelerate research advances used to improve real-time forecasts and services through the Hurricane Forecast Improvement Project (HFIP). HFIP's goals are to reduce the error in track and intensity forecast guidance from numerical model systems by 20% in five years (by 2014) and 50% in 10 years. Additional goals include skillful 7-day forecasts and a greatly increased ability to forecast rapid intensification and decay. For the last six years HFIP tested and evaluated new techniques, including development of higher-resolution and more-realistic global (~20-30 km) and regional (~1-4 km) operational models, advanced data assimilation of inner core observations, higher-resolution global and regional model ensembles, and advanced statistical post processing of model output. Significant advances in track guidance skill have been demonstrated through the use of hybrid data assimilation and in intensity guidance skill from improved regional models and the inclusion of high-resolution data collected within the hurricane. We will present an outline of HFIP and present the most recent results, particularly the components that put into operations in the last year and the impact those changes had on operational model guidance skill.
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