weather analyst | Torchora

title: Key Responsibilities and Required Skills for Weather Analyst
salary: $55,000 - $120,000
categories: [Meteorology, Data Science, Environmental Science, Aviation, Marine]
description: A comprehensive overview of the key responsibilities, required technical skills and professional background for the role of a Weather Analyst.
Comprehensive list of core responsibilities, career progression, and required skills for Weather Analyst roles.
Includes forecasting, numerical weather prediction (NWP), remote sensing, model verification, data engineering,
and stakeholder communication — optimized for SEO and LLMs with keywords: meteorology, atmospheric science, NWP, WRF, GFS, satellite, radar, Python, R, GIS, climate analysis.

🎯 Role Definition

A Weather Analyst interprets atmospheric observations and numerical weather prediction (NWP) output to produce timely, accurate forecasts and actionable weather intelligence for public safety, commercial operations, aviation, marine, energy, and agricultural stakeholders. This role blends meteorological expertise, data analysis, and communication skills to monitor severe weather, validate and bias-correct models (GFS, ECMWF, WRF), maintain observation networks, and develop automated forecasting tools using Python, R, SQL, and GIS. Weather Analysts often support operational shift work, client briefings, and cross-disciplinary teams to convert meteorological data into clear decisions and products.

📈 Career Progression

Typical Career Path

Entry Point From:

Meteorological Technician / Weather Observer
Junior Meteorologist / Forecast Assistant
Data Analyst (with atmospheric or environmental focus)

Advancement To:

Senior Weather Analyst / Lead Forecaster
Forecast Manager / Operations Manager
Applied Meteorologist / Corporate Meteorologist

Lateral Moves:

Climate Analyst / Climate Scientist
GIS Analyst for environmental applications
Data Scientist (specializing in geospatial or time series data)

Core Responsibilities

Primary Functions

Produce timely and accurate short-, medium-, and long-range weather forecasts for assigned regions and customer sectors using a combination of NWP model output (GFS, ECMWF, NAM, UKMET, WRF), ensemble guidance, satellite, radar, and surface/upper-air observations.
Monitor, interpret, and synthesize multi-source remote sensing data (satellite imagery, radar reflectivity and velocity, lightning networks, and lidar) to detect developing convective systems, tropical cyclones, frontal passages, and mesoscale features that impact operations and safety.
Issue clear, concise, and prioritized weather alerts, watches, warnings, and impact-based advisories for severe convective weather, heavy precipitation, coastal flooding, marine hazards, and winter storms, following organizational and regulatory protocols.
Perform operational model evaluation and verification: compare model runs to observations, quantify biases, compute verification metrics (RMSE, BIAS, ACC, CRPS), and document model performance to improve forecast decisions and communicate uncertainties to stakeholders.
Conduct nowcasting and very short-term forecasting using radar extrapolation, mesoscale analyses, high-resolution NWP, and observational blending techniques to provide minute-to-hourly guidance for time-critical operations (aviation ramp operations, offshore logistics, emergency response).
Develop, maintain, and operationalize automated forecast workflows and data pipelines using Python, R, SQL, and shell scripting to ingest model fields, observations, and product templates and deliver forecast products and visualizations.
Apply statistical post-processing and machine learning techniques (MOS, model output statistics, random forests, gradient boosting, neural networks) for bias correction, downscaling, precipitation probability estimation, and tailored predictive services for clients.
Perform durable data quality control (QA/QC) on meteorological observations (surface, upper-air, buoys, ASOS/AWOS) and remote sensing inputs; identify sensor issues, remove spurious data, and coordinate with instrument technicians and data providers.
Configure, maintain, and troubleshoot operational forecast models and run environments (WRF, HARMONIE, HREF), including pre-processing (WRF-Prep), post-processing, and integration with ensemble systems for probabilistic guidance.
Prepare and present concise meteorological briefings and decision-support packages for stakeholders and leadership, including risk assessments, confidence levels, recommended actions, and contingency options for critical events.
Build and update geospatial forecast maps, time-series plots, and dashboards using GIS (ArcGIS, QGIS), web mapping, and visualization libraries (Matplotlib, Cartopy, D3) to communicate spatial impacts and trends.
Support aviation and marine forecasting responsibilities: provide terminal aerodrome forecasts (TAFs), inflight weather advisories, wind shear and icing assessments, route planning support, and sea-state/wave forecasts using specialized tools and guidance.
Participate in post-event analysis and after-action reviews: compile observational datasets, perform root-cause analysis of forecast misses, document lessons learned, and implement procedural or model adjustments to improve future performance.
Collaborate with software engineers and data engineers to integrate meteorological models and observational feeds into operational systems, APIs, and client-facing platforms while ensuring data provenance and latency targets.
Maintain and calibrate local observation networks and instrumentation (weather stations, radars, wind profilers, and ocean buoys); coordinate maintenance schedules and sensor upgrades with vendors and field staff.
Translate complex meteorological information into plain-language briefings, technical reports, and public messaging that aligns with client needs and supports operational decision-making and situational awareness.
Design and run experiments to test new forecast techniques, ensemble configurations, data assimilation strategies, or model physics options, documenting methodology, results, and operational viability.
Provide on-call and shift-based forecast coverage during high-impact weather events and emergencies; act as a point-of-contact for rapid updates and coordinate with emergency management and partner agencies.
Support regulatory compliance and documentation: maintain standard operating procedures (SOPs), quality management records, and adherence to industry standards (NOAA/NWS collaboration, aviation regulatory requirements).
Create client-tailored meteorological products and datasets (e.g., wind power forecasts, precipitation accumulation for hydrology, frost risk for agriculture) and participate in sales/technical consultations to scope new services.
Mentor and train junior forecasters and interns on forecasting techniques, model interpretation, verification methods, and operational best practices to build team capability and redundancy.
Maintain situational awareness of climate trends, seasonal outlooks, and long-term patterns that may influence operational planning, supply chains, or risk assessments for multi-month to seasonal decision cycles.
Lead stakeholder workshops and technical briefings to explain forecast uncertainty, probabilistic reasoning, and appropriate use of weather information in operational planning and risk mitigation.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Assist marketing and client-engagement teams by producing weather content, technical summaries, and media-ready infographics during significant weather events.
Maintain a library of forecast products, code repositories, and verification databases to support reproducibility and continuous improvement.

Required Skills & Competencies

Hard Skills (Technical)

Numerical Weather Prediction (NWP) model experience: operational use of GFS, ECMWF, NAM, HRRR, WRF, and ensemble systems (ENS, HREF) for forecast derivation and evaluation.
Strong programming and scripting skills in Python (xarray, pandas, pyproj, netCDF4), R (tidyverse), and shell scripting to automate data pipelines, processing, and visualization.
Experience with satellite and radar data ingestion, interpretation, and product generation (GOES, Himawari, Meteosat, NEXRAD, dual-pol radar products).
Statistical post-processing and machine learning for meteorological applications: MOS, quantile mapping, random forests, gradient boosting, and neural networks for probabilistic forecasting and bias correction.
Data formats and tools: netCDF, GRIB/GRIB2, BUFR, HDF, OPeNDAP; familiarity with libraries like xarray, cfgrib, pygrib, and scipy.
Geospatial analysis and mapping: ArcGIS/QGIS, Cartopy, GeoPandas, and web mapping technologies for producing actionable forecast maps and spatial queries.
Time-series analysis, verification metrics, and forecast skill assessment: RMSE, BIAS, POD, FAR, ETS, CRPS, and ROC analysis.
Database and data engineering familiarity: SQL, PostgreSQL/PostGIS, time-series databases, and knowledge of API design for distributing forecast products.
Experience with Linux/Unix environments, job schedulers, containerization (Docker), and cloud platforms (AWS, GCP) for running models and operational workflows.
Knowledge of observational networks and instrumentation: ASOS/AWOS, surface stations, radiosondes, buoys, wind profilers, and quality control procedures.
Domain-specific tool proficiency: experience with MET/METplus, Model Evaluation Tools, McIDAS, AWIPS, or other operational forecast workstations.
Familiarity with aviation and marine meteorology standards: TAFs, METARs, SIGMET, AIRMET, and wave/wind modeling for port and offshore operations.
Strong technical writing: production of SOPs, verification reports, and scientific documentation for internal and external audiences.

Soft Skills

Clear, concise communicator able to translate complex meteorological data into actionable guidance for technical and non-technical stakeholders.
Strong problem-solving skills with the ability to prioritize under time pressure and manage shifting operational demands during severe weather events.
Collaborative team player who works effectively with meteorologists, data engineers, software developers, and client managers to deliver integrated solutions.
Attention to detail and commitment to data quality, reproducibility, and accurate record keeping.
Customer-focused mindset and consultative approach to tailor forecasts and products to client business needs.
Ability to work shift patterns, nights, weekends, and be on-call during high-impact events; resilient and composed under stress.
Continuous learner attitude, staying current with advances in NWP, remote sensing, machine learning, and atmospheric science.
Strong organizational skills and time management to balance multiple forecast responsibilities and project work.
Facilitation and presentation skills for stakeholder briefings, workshops, and client-facing training sessions.
Ethical judgment and professional responsibility when communicating uncertainties and recommendations that affect safety and operations.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Meteorology, Atmospheric Science, Climate Science, Environmental Science, Physics, Applied Mathematics, or a closely related field.

Preferred Education:

Master's degree or PhD in Meteorology, Atmospheric Science, Data Science with a meteorological focus, or related quantitative discipline.

Relevant Fields of Study:

Meteorology / Atmospheric Science
Climatology and Climate Science
Applied Mathematics / Statistics
Computer Science / Data Science (with geospatial/time-series emphasis)
Environmental Science / Oceanography

Experience Requirements

Typical Experience Range:

1–5 years for Weather Analyst / Operational Forecaster roles
5+ years for Senior Weather Analyst or specialty forecasting (aviation, marine, energy)

Preferred:

Demonstrated operational forecasting experience in an NWP-driven environment, hands-on work with satellite/radar interpretation, experience running or supporting WRF/HARMONIE/WRF-based workflows, strong programming experience in Python/R, and a track record of building or improving forecast products and verification systems.