William (Bill) Ramstrom
Senior Software Engineer (University of Miami/CIMAS), Hurricane Research Division
305.361.4433
4301 Rickenbacker Causeway
Miami, Florida 33149
William (Bill) Ramstrom is a Senior Software Engineer through the University of Miami’s Cooperative Institute of Marine and Atmospheric Studies (CIMAS) for the Hurricane Research Division at AOML.
Current Work
Senior Software Engineer (University of Miami/CIMAS), Hurricane Research Division
- Ramstrom, W., X. Zhang, K. Ahern, and S. Gopalakrishnan. Implementation of storm-following nest for the next generation Hurricane Analysis Forecast System (HAFS). Frontiers in Earth Science, 12:1419233, https://doi.org/10.3389/feart.2024.1419233 2024
Ref. 4457 - Hazelton, A., G.J. Alaka, Jr., L. Gramer, W. Ramstrom, S. Ditchek, X. Chen, B. Liu, Z. Zhang, L. Zhu, W. Wang, B. Thomas, J.H. Shin, C.-K. Wang, H.-S. Kim, X. Zhang, A. Mehra, F. Marks, and S. Gopalakrishnan. 2022 real-time hurricane forecasts from an experimental version of the Hurricane Analysis and Forecast System (HAFSV0.3S) Frontiers in Earth Science, 11:1264969, https://doi.org/10.3389/feart.2023.1264969 2023
Ref. 4331 - Poyer, A., W. Komaromi, S. Gopalakrishnan, L. Wolf, F. Marks, G. Alaka Jr., J. Anderson, V. Tallapragada, M. Brennan, A. Mehra, X. Zhang, Z. Zhang, A. Hazelton, D.A. Zelinsky, J.L. Franklin, A. Aksoy, C. Alexander, M. Bender, L. Bernardet, M. Biswas, J. Cangialosi, M. DeMaria, R. Dunlap, M. Ek, G. Eosco, L. Gramer, L. Harris, J.S. Hilderbrand, E. Kalina, H.-S. Kim, P. Kucera, B. Liu, P. McCaslin, T. Marchok, J. Moskaitis, K. Musgrave, L. Nance, K. Newman, M. Onderlinde, W. Ramstrom, D. Rosen, J. Sims, J. Sippel, D. Stern, R. Torn, X. Wang, W. Wang, Y. Weng, B.C. Zachry, C. Zhang, M. Zhang, and L. Zhu. 2021-2022 HFIP R&D activities summary: Recent results and operational implementation. HFIP Technical Report, HFIP-2023-1, 73 pp., https://doi.org/10.25923/exgj-1n68 2023
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March 2022 NOAA OAR Team Member of the Month
For contributions that have improved hurricane structure and intensity predictions that will greatly benefit the public and emergency managers in their decision-making.