Satellite Data Assimilation and Fire Weather Modeling Specialist; Scientist IV

Overview

As wildfires increasingly reshape the weather around them, NOAA needs modeling systems that can keep up. As FWI's Satellite Data Assimilation and Fire Weather Modeling Specialist supporting NSSL's Warn-on-Forecast (WoFS) initiative, you will develop and advance convective- and meso-scale atmospheric modeling systems — within the MPAS and/or WRF frameworks — that integrate satellite and in-situ observations through ensemble-based data assimilation to better predict fire behavior, smoke transport, and aerosol impacts.

This is high-performance-computing science with real operational stakes: your work will help the National Weather Service better forecast how fire and atmosphere interact.

As wildfires increasingly reshape the weather around them, NOAA needs modeling systems that can keep up. As FWI's Satellite Data Assimilation and Fire Weather Modeling Specialist supporting NSSL's Warn-on-Forecast (WoFS) initiative, you will develop and advance convective- and meso-scale atmospheric modeling systems — within the MPAS and/or WRF frameworks — that integrate satellite and in-situ observations through ensemble-based data assimilation to better predict fire behavior, smoke transport, and aerosol impacts.

This is high-performance-computing science with real operational stakes: your work will help the National Weather Service better forecast how fire and atmosphere interact.

Remote This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST.

• Develop, modify, and maintain components of advanced atmospheric modeling systems within MPAS and/or WRF frameworks
• Implement and evaluate ensemble-based data assimilation methodologies for integrating satellite and in situ observations into fire, smoke, and aerosol prediction systems
• Conduct research and development activities to improve fire behavior, smoke transport, and aerosol parameterizations in numerical weather prediction models
• Design, execute, and analyze convective- and meso-scale modeling experiments using high-performance computing (HPC) resources
• Develop workflows and software tools using Git, Python, Bash, Fortran, and related technologies to support model development, testing, and evaluation
• Analyze model performance and observational datasets to identify opportunities for improving forecast skill and physical representation of fire-atmosphere processes
• Collaborate with multidisciplinary research teams to support development of next-generation fire and smoke forecasting capabilities
• Prepare technical documentation, code repositories, validation reports, and workflow descriptions to support research and operational activities
• Contribute to project reporting requirements, including quarterly and annual progress reports
• Lead or contribute to peer-reviewed scientific publications and present research findings at national and international conferences, workshops, and stakeholder meetings

• MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or a related field
• 8+ years of professional or academic experience

• Experience with convective-scale and/or meso-scale numerical weather prediction modeling
• Demonstrated expertise in ensemble-based data assimilation techniques
• Prior experience in fire, smoke, and/or aerosol modeling and prediction
• Proficiency modifying and developing code within MPAS, WRF, or similar atmospheric modeling frameworks
• Advanced programming experience using Python, Bash, Fortran, Git, and related scientific software tools
• Experience utilizing complex modeling systems in high-performance computing (HPC) environments
• Understanding of aerosol, fire, and smoke parameterization schemes and their…