Session 12 Hurricane Analysis and Forecast System [HAFS]: Research Development and Operational Implementation


Description:

This session is an open invitation for all speakers to present their work related to Hurricane Forecast Improvement Program strategic goals: improving hurricane research, observations, UFS Hurricane modeling, forecasting, and communicating hurricane risks to all audiences.
The Hurricane Analysis and Forecasting System (HAFS) is NOAA’s next-generation, multi-scale numerical model and data assimilation package, which will provide operational analysis and forecast out to seven days. HAFS will provide reliable and skillful guidance on Tropical Cyclone (TC) track and intensity (including RI), storm size, genesis, storm surge, rainfall, and tornadoes associated with TCs. The initial operational capacity of HAFS was approved by National Weather Service (NWS) for operational implementation for the 2023 hurricane season. HAFS comprises five major components: (1) storm-following telescopic moving nests, (2) high-resolution physics configured for TC application, (3) multi-scale Data Assimilation (DA) with vortex initialization, (4) full three-way atmosphere-ocean-wave coupling framework,and (5) intensive hurricane observational platforms to support the multi-scale DA system, the physics packages evaluation and improvement, and forecast verifications.
Conveners: Sundararaman Gopalakrishnan, NOAA/AOML/HRD and
                   Aaron Poyer, NOAA/NWS/STI


Papers:
Hurricane Forecast Improvements
Sundararaman Gopalakrishnan, AOML, Miami, MA; and A. J. Poyer, Z. Zhang, G. J. Alaka Jr., and W. A. Komaromi

HAFS-Basin: Development of a Multi-Storm Configuration to Improve Tropical Cyclone Forecasts
Ghassan J. Alaka Jr., NOAA/AOML/HRD, Miami, FL; and W. Ramstrom, M. C. Ko, L. J. Gramer, A. Hazelton, S. Gopalakrishnan, B. Liu, Y. Weng, and J. H. Shin

HAFS Ensemble Data Assimilation and Prediction - A Real Time Experiment for North Atlantic Basin in 2023
Yonghui Weng, Lynker at NOAA/NWS/NCEP/EMC, College Park, MD; and Z. Zhang, W. Wang, B. Liu, J. Cheng, L. Zhu, J. A. Sippel, A. Aksoy, J. Poterjoy, X. Wang, A. Mehra, and V. S. Tallapragada

Real-time Testing of Experimental Upgrades to the Hurricane Analysis and Forecast System, Version B (HAFSV1.1B)
Andrew T. Hazelton, University of Miami CIMAS, Miami, FL; and G. J. Alaka Jr., X. Chen, M. C. Ko, W. Ramstrom, Z. Zhang, B. Liu, W. Wang, C. K. Wang, X. Zhang, L. Bengtsson, V. S. Tallapragada, and S. Gopalakrishnan

Evaluation of the coupled MOM6 ocean model component during the 2023 HAFS real-time experiments
John D. Steffen, PhD, SAIC at NOAA/NWS/NCEP/EMC, College Park, MD; and M. Aristizabal, B. Li, Y. Li, L. J. Gramer, H. Kang, H. S. Kim, B. Liu, Z. Zhang, and A. Mehra

The Hurricane Forecast Improvement Program (HFIP): Recent Advances and Looking Ahead to 2024 and Beyond
William A. Komaromi, NWS, Ellicott City, MD; NWS, Silver Spring, MD; and A. J. Poyer, S. Gopalakrishnan, F. D. Marks Jr., ScD, V. S. Tallapragada, A. Mehra, M. J. Brennan, J. R. Rhome, K. Garrett, G. M. Eosco, Ph.D, and J. S. Lee

Impact of Adjusting the Deep Convection Parameterization on HAFS Intensity Forecast Improvement
JungHoon Shin, Lynker at NOAA/NWS/NCEP/EMC, College Park, MD; Lynker at NOAA/NWS/NCEP/EMC, College Park, MD; and B. Liu, Z. Zhang, J. Han, A. Mehra, and V. S. Tallapragada

Evaluating Tropical Cyclone Intensity Forecasts in the North Atlantic Using the NOAA Next-Generation Enterprise Ocean Heat Content Algorithm
Deirdre A. Byrne, NOAA/STAR, College Park, MD; and P. Lavin, D. S. Trossman, and L. J. Gramer

Submission Deadline: Thursday, 31 August 2023