M.S. in atmospheric sciences, meteorology, scientific programming, mathematics, or related field with 7+ years of experience in numerical model analysis.
Experience with object-oriented verification techniques (e.g., METplus MODE) and high-resolution NWP model evaluation.
Proficient in Python within a high-performance computing (HPC) UNIX environment for verification metrics and visualizations.
Skilled in using GitHub for software repository management and collaborative projects.
Familiar with meteorological data formats (GRIB2, NetCDF, HDF, BUFR) and model verification software (specifically METplus).
Strong communication skills for technical results across interagency teams and operational forecasters.
Some knowledge of web technologies (HTML, JavaScript) for displaying verification data.
Responsibilities
Investigate and apply object-oriented verification methods to evaluate high-resolution model performance.
Collaborate with developers to create automated verification workflows for convective-scale models.
Act as a technical liaison on verification topics between the Weather Prediction Center and EVU/OMD.
Develop advanced metrics for high-resolution AI/ML model verification and evaluation.
Contribute to the METplus verification framework with innovative metrics and code enhancements.
Support the Model Evaluation Group and interact with NWS/NCEP domain scientists, adhering to NOAA/NWS IT policies.
Present findings at technical and status meetings.
Benefits
Collaborative work environment with a focus on innovation.
Opportunity to contribute to community-based software frameworks.
Engagement with cutting-edge AI-driven forecasting systems.
Professional development through interaction with interagency teams and operational forecasters.
Full Job Description
Overview
Lynker, a Federal Government Contractor, is seeking talented Physical Scientist for EVU Regional Verification to join the Evaluation and Verification Unit (EVU) within the NOAA/NWS Office of Modeling and Development (OMD). Working in a fast-paced, highly collaborative environment, this position will advance object-oriented verification techniques, support customized workflows for regional and convective-scale models, and evaluate next-generation AI-driven forecast systems. The scientist will serve as a key technical liaison for quantitative precipitation forecasting (QPF) verification topics while contributing to the community-based METplus software framework and supporting operational model evaluation efforts.
Responsibilities
Duties of the Physical Scientist for EVU Regional Verification will include the following:
Object-Oriented & High-Resolution Model Verification: Investigate and apply object-oriented verification methods (e.g., METplus MODE) to evaluate high-resolution model performance and improve spatial skill assessment.
Convective & Rapid-Refresh Workflow Development: Work closely with developers on systems like RRFS, REFS, and WoFS to create customized, automated verification workflows tailored specifically for model development purposes.
Interagency & Operational Liaison: Act as a key technical liaison between the Weather Prediction Center (WPC) and EVU/OMD on National Blend of Models (NBM) and National Digital Forecast Database (NDFD) verification topics, with a primary focus on quantitative precipitation forecasting (QPF).
AI & Next-Gen Model Evaluation: Develop advanced metrics and methods for high-resolution AI/ML model verification and evaluation (e.g., HRRRCast).
Community Software & METplus Collaboration: Actively support and contribute innovative verification metrics, code enhancements, and graphics capabilities to the community-based METplus verification framework.
Operational & Science Team Support: Support the team's Model Evaluation Group (MEG) efforts, interact with NWS/NCEP domain scientists, adhere to NOAA/NWS IT policies, and regularly present findings at technical and status meetings.
Qualifications
The Physical Scientist for EVU Regional Verification selected should have the following:
An M.S. (or equivalent experience) in atmospheric sciences, meteorology, scientific programming, mathematics, or a related physical science with 7+ years of experience in numerical model analysis, evaluation, or verification.
Demonstrated experience using object-oriented verification techniques (such as METplus MODE) and evaluating high-resolution numerical weather prediction (NWP) models.
Extensive experience working with Python in a high-performance computing (HPC) UNIX environment to calculate verification metrics and generate custom visual plots.
Demonstrated proficiency using GitHub to manage software repositories, code versions, and collaborative projects.
Proven experience working with common meteorological data formats (e.g., GRIB2, NetCDF, HDF, BUFR) and model verification software systems (specifically METplus).
Strong team-player mindset with demonstrated skill in communicating technical results effectively across interagency teams, developers, and operational forecasters.
Some knowledge of using web page technology and common languages (e.g., HTML, Javascript) to display plots of verification data.
Ability to analyze/plot and verify model output independently.
Ability to work independently and collaboratively on complex problems.
The Ideal Physical Scientist for EVU Regional Verification will have the following:
Experience developing customized verification workflows or evaluation tools for convective-scale/rapid-refresh models and ensembles (e.g., RRFS, REFS, WoFS, or HRRR).
Familiarity with evaluating AI/ML weather models (e.g., HRRRCast) or developing new metrics for machine learning forecast systems.
Experience in precipitation verification topics (QPF) and working with operational datasets/systems like the National Blend of Models (NBM) or National Digital Forecast Database (NDFD).
Knowledge of Fortran, web technologies (HTML, JavaScript) for web page plotting, or legacy display tools (GrADS, GEMPAK, MATLAB).
Familiarity with National Weather Service operational centers, OMD workflows, or operational forecasting environments.
Ability to work in a fast-paced environment.
Demonstrated skill in performing tasks requiring organization and attention to detail.
Knowledge of statistical principles and strong analytical skills.
A passion for the National Weather Service mission.
Ability to accept assigned tasking, but also engage as a creative self-starter.
Driven by curiosity and willing to try new techniques and learn new skills.
Ability to remain flexible as projects and tasks evolve.
