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The Cooperative Institute for Marine and Atmospheric Studies (CIMAS) of the University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science has an exciting opportunity for a full-time Post-Doctoral researcher position based in Miami, Florida. This position is supported for a period of two years through a project funded by the NOAA Global Ocean Monitoring and Observing (GOMO) program.
The primary objective of this role is to undertake a comprehensive investigation to quantify the impact of various ocean observations on the accuracy and robustness of the Marine JEDI analysis system. A main focus involves systematically evaluating how the assimilation of diverse oceanographic data affects the initial state of the ocean models. This analysis is fundamental to understanding and ultimately enhancing the skill of coupled ocean-atmosphere models used for tropical cyclone and hurricane prediction. The incumbent is expected to: (1) Perform ocean Observing System Experiments (OSEs) to assess the impact of ocean observations, particularly in-situ observations from various platforms, such as gliders, on ocean analysis; (2) Conduct ocean OSEs for hurricane forecasts, using weakly coupled data assimilation integrated into the coupled Hurricane Analysis and Forecast System (HAFS). The appointee will work closely with scientific advisors at the PhOD, as well as partners at the Hurricane Research Division of NOAA/AOML and at the Environmental Modeling Center (EMC) of the U.S. National Weather Service.
Department Specific Functions
Duties include but are not limited to:

• Improve existing high-resolution Modular Ocean Model version6 (MOM6) regional model to minimize model errors.
• Conduct MOM6 analysis using the Marine JEDI data assimilation (DA) system with a variational DA approach.
• Perform ocean OSEs, with various DA cycling and different data windows, and conduct hurricane predictions using the coupled Hurricane Analysis and Forecast System (HAFS).
• Analyze results and present findings in scientific meetings and publish results in peer-reviewed journals.

Minimum Qualifications

• Applicants must have a Ph.D. in oceanography, applied mathematics, statistics or closely related discipline.
• Required skills include a demonstrated experience with running numerical ocean, atmosphere, or coupled Earth system model, and/or data assimilation, and also include trouble shooting capabilities.
• Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance computing environments, and GPU programming.
• Necessary skills include knowledge of data processing using software (e.g., Matlab, R, IDL) and/or statistical/mathematical programming languages (e.g., R, Matlab, Python).
• The incumbent must have a proven publication record, scientific writing skills, and communication skills.
• The successful candidate must be able to work independently as well as collaboratively with internal and external partners.

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Job Status:
Full time
Employee Type:
Staff