Develop and maintain advanced atmospheric modeling systems within MPAS and WRF frameworks to improve fire, smoke, and aerosol predictions. Conduct research using high-performance computing to integrate satellite and in-situ observations into ensemble-based data assimilation workflows.
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.
Work Schedule and Location:
Remote: This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST.
Responsibilities
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
Qualifications
Required:
MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or a related field
8+ years of professional or academic experience
Desired:
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 application within numerical models
Demonstrated ability to communicate scientific results through presentations, technical reports, and peer-reviewed publications
Ability to work effectively as part of an interdisciplinary research and development team
Work Setting and Environment:
Primary location: Remote
Normal work hours are Monday through Friday, 8 hours per day / 40 hours per week, excluding federal holidays; field data-collection activities may require irregular hours during active severe weather events
Local and non-local travel may be required, not anticipated to exceed 5% annually; all unplanned travel must be approved in writing by the COR at least 10 calendar days in advance
Must complete an online IT security awareness course within one week of starting work
Foreign national candidates are subject to export control review and require CO/COR approval prior to consideration
Government-furnished equipment provided, including access to HPC resources, specialized mobile observation platforms, laboratory test equipment, computers, and office workspace, as applicable
Why Join Our Team
At FWI, we place the highest importance on creating an exceptional employee experience. You'll have opportunities to achieve your career aspirations through internal promotions, professional development, and other recognition and rewards programs. Join our team and take advantage of the many benefits we offer, including:
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