Jakir Hossen

Headshot photo of Jakir Hossen.

Research Interests

Evaluate the impact of observing system on ocean forecasts.

Application of machine learning techniques on parameterizations of small scale features of physical processes.

Jakir Hossen, Ph.D.

Project Scientist, Hurricane Research Division


4301 Rickenbacker Causeway
Miami, Florida 33149

Dr. Jakir Hossen is a Project Scientist in the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory (AOML). His research is to evaluate the impact of proposed and existing observation systems on analyses and forecasts of the ocean by assimilating in situ and remote sensing observations. Besides his experiences working with Data assimilation methods, he is interested in machine learning algorithms to estimate parameters of physical processes to improve weather forecasting. 

Current Work

Project Scientist, Hurricane Research Division

Download Full CV

2015, Ph.D., Earth Sciences, Australian National University, Canberra, Australia

2008, M.S., Computational Science, Florida State University, Tallahassee, FL

2001, M.Sc., Applied Mathematics, University of Dhaka, Bangladesh

1999, B.Sc., Mathematics, University of Dhaka, Bangladesh

  • M. J. Hossen, Iyan E. Mulia, David Mencin and Anne F. Sheehan (2020). \ Data assimilation with ship-borne GPS data in the Cascadia subduction zone”, Earth and Space Science, 8, e2020EA001390.
  • M. J. Hossen, A. R. Gusman, K. Satake, & P. R. Cummins (2018). An adjoint sensitivity method applied to time reverse imaging of tsunami source for the 2009 Samoa earthquake. Geophysical Research Letters, 45,627-636.
  • Toshitaka Baba, Sebastien Allgeyer, M. J. Hossen, Phil R. Cummins, Hiroaki Tsushima, Kentaro Imai, Kei Yamashita, Toshihiro Kato (2017), Accurate numerical simulation of the far-field tsunami caused by the 2011 Tohoku earthquake, including the effects of Boussinesq dispersion, seawater density stratification, elastic loading, and gravitational potential change, In Ocean Modeling, Volume 111, Pages 46-54, ISSN 1463-5003.
  • Dettmer J., R. Hawkins, P. R. Cummins, M. J. Hossen, M. Sambridge, D. Inazu, and R. Hino (2016), Tsunami source uncertainty estimation: The 2011 Japan tsunami, J. Geophys. Res. Solid Earth, 121, 4483{4505.
  • M. J. Hossen, I. M. Navon and F. Fang.\A penalized four-dimensional variational data assimilation method for reducing forecast error related to adaptive observations.” International Journal for Numerical Methods in Fluids, 70(10):1207{1220, 2012.