Xuejin Zhang

Research Interests

Numerical model development and application.

Xuejin Zhang, Ph.D.

Meteorologist, Hurricane Research Division


4301 Rickenbacker Causeway
Miami, Florida 33149

Dr. Xuejin Zhang is a Meteorologist employed in NOAA’s Atlantic Oceanographic and Meteorological Laboratory’s Hurricane Research Division. He studies tropical cyclone forecast and simulation, land-air-sea interaction, regional climate, data quality control and homogenization, and parallel computing during his more than two-decade career. His expertise is in numerical algorithms, atmospheric dynamics, model initialization, and microphysics parameterization. He is currently leading the NOAA’s Unified Forecast System (UFS) R2O Hurricane Application Team.

Current Work

Meteorologist, Hurricane Research Division

Download Full CV

2007, Ph.D., Atmospheric Science, North Carolina State University, Raleigh, NC

1996, M.S., Synoptic Dynamics, Chinese Academy of Meteorological Sciences, China

1991, B.S., Climatology, Nanjing Institute of Meteorology (now known as Nanjing University of Information Science and Technology), China

  1. 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
  2. Alaka, G.J. Jr., X. Zhang, and S.G. Gopalakrishnan. High-definition hurricanes: Improving forecasts with storm-following nests. Bulletin of the American Meteorological Society, 103(3):E680-E703, https://doi.org/10.1175/BAMS-D-20-0134.1 2022
    Ref. 4037
  3. Hazelton, A., K. Gao, M. Bender, L. Cowan, G.J. Alaka Jr., A. Kaltenbaugh, L. Gramer, X. Zhang, L. Harris, T. Marchok, M. Morin, A. Mehra, Z. Zhang, B. Liu, and F. Marks. Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD. Weather and Forecasting, 37(1):143-161, https://doi.org/10.1175/WAF-D-21-0102.1 2022
    Ref. 4041

2014 South Florida Federal Executive Board Federal Employee of the Year Award

For contributions toward the development of the advanced, high-resolution Hurricane Weather Research and Forecasting (HWRF) model used operationally to provide forecast guidance to the National Hurricane Center.

May 2013 NOAA Team Member of the Month

For contributions in support of NOAAʼs Hurricane Weather Research and Forecasting (HWRF) high resolution computer model.

2012 NOAA Federal Employee of the Year Award

For innovative work on the NCEP/EMC hurricane forecast model, leading to greatly improved hurricane track and intensity forecasts.

2012 AOML Certificate of Appreciation

2009 AOML Certificate of Merit