Earth & Atmospheric Sciences — P1
EARTHA.EARTHATM14D0.P1
Studies the physical processes of the atmosphere and solid earth to observe, model, and forecast weather, climate, and geophysical phenomena. Spans operational forecasting (interpreting WRF/GFS/ECMWF output, issuing advisories and warnings), instrumentation and field measurement (weather balloons, radar, satellites, seismographs, gravimeters, magnetometers), and computational science (numerical weather/climate modeling, data assimilation, and ML in HPC environments). Distinct from purely data-engineering or software roles by its grounding in geophysical fluid dynamics and atmospheric/earth physics; distinct from hydrology-only and pure-academic-teaching focuses.
Studies the physical processes of the atmosphere and solid earth to observe, model, and forecast weather, climate, and geophysical phenomena. Spans operational forecasting (interpreting WRF/GFS/ECMWF output, issuing advisories and warnings), instrumentation and field measurement (weather balloons, radar, satellites, seismographs, gravimeters, magnetometers), and computational science (numerical weather/climate modeling, data assimilation, and ML in HPC environments). Distinct from purely data-engineering or software roles by its grounding in geophysical fluid dynamics and atmospheric/earth physics; distinct from hydrology-only and pure-academic-teaching focuses.
Focus — Earth & Atmospheric Sciences
Studies the physical processes of the atmosphere and solid earth to observe, model, and forecast weather, climate, and geophysical phenomena. Spans operational forecasting (interpreting WRF/GFS/ECMWF output, issuing advisories and warnings), instrumentation and field measurement (weather balloons, radar, satellites, seismographs, gravimeters, magnetometers), and computational science (numerical weather/climate modeling, data assimilation, and ML in HPC environments). Distinct from purely data-engineering or software roles by its grounding in geophysical fluid dynamics and atmospheric/earth physics; distinct from hydrology-only and pure-academic-teaching focuses.
Responsibilities by level
What this person actually does at each level on the professional track — escalating scope, not one generic blob. Your level is highlighted.
- Collects atmospheric data and field samples under senior supervision using instruments such as weather balloons, radar systems, and surface observation stations
- Takes routine measurements of temperature and air pressure in the atmosphere following defined protocols
- Interprets weather model output to produce basic forecasts under close review
- Prepares for field visits and writes observation reports under senior supervision
- Prepares reports and presentations to communicate preliminary findings to the immediate team
- Analyzes meteorological data from satellite imagery, radar, and surface observations applying defined procedures with routine independence
- Conducts research on changes in the atmosphere and potential causes, documenting methods and results
- Runs and interprets established forecasting models (WRF, GFS, ECMWF) on standard scenarios under general instruction
- Collaborates with senior scientists to refine climate models and processes geospatial datasets using xarray, NetCDF, and pandas
- Produces draft forecast products and advisories for senior review, exercising judgment in familiar atmospheric contexts
- Owns and prepares forecast products, advisories, and warnings, exercising independent judgment on impactful assignments with milestone review
- Analyzes diverse meteorological datasets from multiple sources to evaluate identifiable factors and resolve forecasting problems
- Develops and implements advanced forecasting model configurations (WRF, GFS, ECMWF), planning own work day-to-day
- Mentors junior meteorologists and interns on data collection and analysis methods
- Coordinates project activities with emergency services or media and networks with senior professionals across agencies
- Leads design, development, and testing of new data collection systems and analysis software, conducting in-depth analysis of complex atmospheric variables
- Provides expert consultation on atmospheric and geophysical datasets to agencies and clients, selecting appropriate methods and models
- Interprets complex data for external partners and policymakers, coordinating across modeling, instrumentation, and operations groups
- Directs activities of a meteorology or modeling section as first-line supervisor, leading project teams
- Approves findings and reports and delivers scientific presentations at conferences and stakeholder meetings
- Drafts research proposals and serves as Principal Investigator on grants and contracts, acting independently on broad and special assignments
- Drives the scientific agenda across geophysical fluid dynamics, numerical modeling, and machine learning to advance company objectives
- Develops a measurement portfolio and deploys/analyzes instrumentation (radar, satellites, gravimeters, magnetometers) addressing strategic intangibles
- Serves as external spokesperson and builds influential networks with policymakers, funding bodies, and the scientific community
- Supervises research personnel on specialized scientific tasks and provides strategic planning and mentorship as a named deliverable
- Serves as Chief Meteorologist or lead scientist, holding ultimate authority for forecast products, accuracy, and scientific content
- Leads a large observational sub-group or scientific team and supervises MS/PhD students, postdocs, and research personnel
- Secures funding and wins competitive grants, shaping the organization's long-term scientific direction across physics and ML
- Carries the deepest technical specialization, defining field-shaping approaches to data assimilation, numerical modeling, and HPC deployment
- Performs managerial duties including work schedules, staff training, and high-level mentorship that influences peer professionals and the wider field
Level guidelines
The universal leveling rubric applied to this function — how scope, complexity, collaboration, and experience step up across levels.
| Level | Knowledge & Application | Complexity & Problem Solving | Collaboration & Interaction | Typical Degree & Years |
|---|---|---|---|---|
| P1 | Applies foundational knowledge of calculus, physics, and atmospheric science to routine data collection and basic forecast interpretation; learning to use instruments and standard model output. | Handles routine problems with standard answers following established measurement and reporting protocols. | Maintains stable internal relationships within the immediate team; communicates preliminary findings to supervising scientists. | 0–1 years; new graduate or intern with a degree in meteorology, atmospheric science, or geoscience. |
| P2 | Applies working knowledge of geophysical analytical methods, scientific programming (Python/R), and geospatial tooling (xarray, NetCDF, pandas) to conventional analysis and forecasting tasks. | Solves moderate problems exercising judgment in familiar atmospheric contexts using defined procedures and established models. | Builds productive project relationships with senior scientists; may informally guide interns. | 2+ years with a BA/BS, or an MS/PhD with no prior experience. |
| P3 | Applies in-depth knowledge of numerical weather modeling, data assimilation, and remote sensing to diverse problems; configures and adapts WRF/GFS/ECMWF independently. | Evaluates identifiable factors across diverse datasets to resolve forecasting and analysis problems with moderate independence. | Networks with senior professionals and coordinates project activities with emergency services, media, and partner agencies. | 5+ years with a BA/BS, 3+ years with an MA/MS, or a PhD without prior experience. |
| P4 | Applies expert knowledge of geophysical fluid dynamics, ML in HPC environments, and instrumentation design to complex issues with functional impact; selects methods and tools. | Conducts in-depth analysis of complex, interdependent atmospheric and geophysical variables; designs new tools rather than only operating existing ones. | Coordinates across modeling, instrumentation, and operations groups; influences decisions of external partners and policymakers; first-line supervision. | 8+ years, often with graduate education in atmospheric or earth sciences. |
| P5 | Applies authoritative expertise spanning physics-based modeling and machine learning to strategic, often ambiguous problems contributing to company objectives. | Resolves strategic issues and intangibles with high independence; defines scientific approaches across multiple domains. | Builds influential networks; serves as external spokesperson with funding bodies, agencies, and the scientific community; owns funding as Principal Investigator. | 12+ years with extensive expertise; PhD typical. |
| P6 | Applies field-defining, visionary expertise across geophysical physics and ML, holding the deepest technical specialization and ultimate scientific authority. | Solves field-shaping problems with full independence; sets the scientific agenda and methodological standards for the organization. | Influences industry and company direction as a recognized thought leader; provides high-level mentorship to peer professionals and leads large scientific teams. | 15+ years as a principal expert; PhD plus established scientific and industry leadership. |
Skills
Focus-specific skills the role applies — the relevance layer beyond the occupational base.
- Scientific programming
- Proficiency in Python, R, or MATLAB for data analysis and modeling.
- Geospatial data processing
- Familiarity with tools such as xarray, NetCDF, and pandas for processing and visualizing geospatial data.
- Numerical weather/climate modeling
- Expertise in atmospheric modeling tools such as WRF, GCMs, and similar physics-based systems.
- Machine learning
- Proficiency in ML libraries such as PyTorch or Jax, including deploying models in HPC environments.
- Remote sensing
- Use of satellite, radar, and remote sensing technologies to monitor weather and collect data.
- GIS
- Geographic information systems for data visualization and spatial analysis.
- High-performance computing
- Comfort deploying machine learning and physics models in HPC environments.
- Mathematical/physical foundations
- Strong foundations in calculus, differential equations, statistics, physics, and chemistry.
- Geophysical analytical methods
- Analyzing climate datasets using geophysical fluid dynamics, data assimilation, or numerical modeling.
- Communication
- Ability to communicate findings to nonscientist and policymaker audiences.
- Version control
- Use of Git for managing code in research and modeling work.
Provenance
The evidence base behind this profile — every layer is sourced; quality is scored by an adversarial review panel (1–5; passes at ≥4 on the minimum dimension).
Level — P1 — Entry-Level Professional
New to role or field; performs basic tasks under supervision
- Scope
- Own tasks within a defined component
- Autonomy
- Close supervision; work reviewed frequently
- Complexity
- Routine problems with known solutions
- Impact
- Own deliverables
- Decision rights
- Few independent decisions; escalates the rest
- Leadership
- None — building the craft
- Typical experience
- 0–2 yrs
Adjacent roles
Nearest roles by structural coordinates (level + taxonomy). Distance 0 → 1; each carries its 3-state match band. How coordinates work → · Compare side-by-side →
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- code=19-2099source=jfm-factory.resolve