5.1 Advanced Analysis and Prediction of Hurricane Harvey with NOAA’s Newly Developed NGGPS Model and Assimilation of the Newly Launched GOES-16 All-Sky Radiance

Tuesday, 9 January 2018: 10:30 AM
Ballroom D (ACC) (Austin, Texas)
Fuqing Zhang, Pennsylvania State Univ., State College, PA; and X. Chen, M. Minamide, R. Nystrom, S. J. Lin, and L. Harris

Hurricane Harvey brought catastrophic destruction and historical flooding to the Gulf Coast region. Guided by numerical weather prediction models, operational forecasters at NOAA provided outstanding forecasts of Harvey’s future path and potential for record flooding days in advance. These forecasts were valuable to the public and emergency managers in protecting lives and property. The current study shows the great potential for further improving Harvey’s analysis and prediction through (1) advanced ensemble assimilation of unprecedented high-spatiotemporal, all-sky infrared radiances from the newly-launched, next-generation geostationary weather satellite GOES-16, and (2) the experimental next-generation global prediction system (NGGPS) under development at NOAA that has embedded a convection-permitting nested domain over the hurricane with enhanced inner-core initialization ingesting the GOES-16 all-sky radiances. The global-nested NGGPS model not only improves over the current-generation operational models’ track prediction but also provides accurate forecasts of the storm’s structure, its rapid intensification to a major hurricane, and total rainfall along the Gulf Coast region. This study highlights the potential and need for improving hurricane prediction through the nation’s further investments in advanced observing systems such as those from weather satellites, comprehensive data assimilation methodology that can more effectively ingest existing and future observations, higher-resolution weather prediction models with more accurate numerics and physics, and high-performance computing facilities that can perform advanced analysis and forecasting in a timely manner.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner