Key Responsibilities and Required Skills for Weather Manager

🎯 Role Definition

As a Weather Manager, you will lead operational meteorology and weather services for the organization, combining scientific expertise, team leadership, and customer-focused product delivery. This role is responsible for producing reliable forecasts and alerts, managing forecasting teams and observation networks, optimizing numerical weather prediction (NWP) workflows, and ensuring timely coordination with internal stakeholders, customers, and emergency-response partners. The ideal candidate balances hands-on meteorological skill (model interpretation, radar/satellite analysis, verification) with program-level oversight (SLA management, budgeting, vendor relationships, and continuous improvement).

📈 Career Progression

Typical Career Path

Entry Point From:

Senior Operational Meteorologist / Lead Forecaster
Environmental Data Scientist or Atmospheric Research Scientist
Emergency Management Specialist with meteorological experience

Advancement To:

Director of Weather Services
Head of Environmental Operations or Chief Meteorologist
VP of Operations / Senior Director, Climate & Weather Products

Lateral Moves:

Product Manager — Weather & Environmental Solutions
Emergency Management Director (public/private sector)
Lead Data Engineer for Atmospheric Data Platforms

Core Responsibilities

Primary Functions

Lead and manage the daily operational forecasting team to deliver accurate short-, medium-, and long-range weather forecasts, briefings, watches, warnings, and advisories to internal stakeholders and external customers, ensuring 24/7 coverage as required.
Oversee the implementation, tuning, and operational deployment of numerical weather prediction (NWP) models (WRF, GFS, HRRR, ICON, HARMONIE) and ensemble forecasting systems, including configuration, verification cycles, and model bias correction.
Design, own, and continuously improve quality assurance (QA/QC) processes for observational networks (surface stations, upper-air, AWS, radar, satellite) to ensure data integrity for operational forecasting and downstream analytics.
Coordinate severe-weather and high-impact event response protocols with incident commanders, emergency management agencies, and critical infrastructure customers to ensure timely alerts, escalation, and decision support.
Develop and maintain standard operating procedures (SOPs), escalation pathways, and service-level agreements (SLAs) for forecast delivery, watch/warning issuance, and customer support.
Lead the development of customer-facing weather products and decision-support tools (web dashboards, APIs, mobile alerts), translating meteorological insight into actionable guidance for commercial and public-safety users.
Run routine verification, model performance monitoring, and post-event analysis programs to quantify forecast skill, identify failure modes, and prioritize model and process improvements.
Manage vendor relationships for third-party model products, satellite/radar feeds, and instrumentation, including contract negotiation, performance reviews, and integration planning.
Drive data assimilation and observational network improvements by specifying and overseeing the deployment of sensors, radars, buoys, and remote-sensing integrations to close critical observation gaps.
Oversee the implementation of automated forecast production pipelines including data ingestion, model run orchestration, post-processing, and templated product generation using modern CI/CD practices.
Integrate machine learning and statistical post-processing methods (MOS, model output statistics, RF, neural nets) into operational products to reduce systematic errors and improve probabilistic guidance.
Ensure regulatory, safety, and industry compliance for meteorological services, including alignment with national meteorological services (NWS/Met Office/Environment Canada) and reporting requirements.
Prepare and present executive-level weather risk briefings, operational summaries, and post-incident reports to senior leadership and key customers, focusing on actionable impact and mitigation recommendations.
Recruit, mentor, and develop forecasting staff, including training programs, performance management, career development plans, and succession planning for critical operational roles.
Manage the departmental budget, resource allocation, and procurement for meteorological software, instrumentation, cloud compute, and data subscriptions to maximize operational readiness and ROI.
Maintain and test business continuity and disaster recovery plans for forecast operations, data archives, and communication channels to ensure resilience during high-impact periods.
Lead R&D collaborations with academic and governmental partners to evaluate emerging models, remote sensing products, and improved forecasting techniques for operational adoption.
Drive cross-functional coordination with product, engineering, sales, and legal teams to translate meteorological capabilities into scalable commercial offerings and ensure accurate messaging to customers.
Oversee social media and public communications strategy for weather-related messaging during events, coordinating clear, timely, and compliant statements with communications teams.
Implement verification-driven iteration cycles for probability thresholds and warning criteria to balance false alarms against missed events and optimize customer trust.
Supervise instrumentation maintenance schedules and technical calibration procedures for radars, lidars, and in-situ sensors, ensuring uptime and measurement traceability.
Lead cost-benefit analyses and use-case prioritization for new observational investments, compute capacity expansion, or ML deployments to inform capital planning.
Champion a safety-first culture across forecasting and field teams, incorporating meteorological risk assessments into operations planning and fieldwork authorizations.
Maintain up-to-date documentation, data lineage, and metadata standards to support reproducible analyses, audits, and machine-readability of weather products.

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.
Provide subject-matter expertise for sales proposals, technical onboarding, and customer training sessions on forecast interpretation and decision-making.
Conduct regular tabletop exercises and after-action reviews with partners to validate alerting workflows and communication effectiveness.
Assist in the development of training content and certification paths for new forecasters and partner organizations.
Monitor industry trends (satellite launches, model developments, new assimilation techniques) and recommend adoption strategies to leadership.
Support grant-writing or public-private partnership proposals to fund observational or modeling projects.
Liaise with regulatory and standards bodies to advocate for interoperable weather-data formats and open-source tooling adoption.

Required Skills & Competencies

Hard Skills (Technical)

Operational forecasting and severe weather warning issuance (short-, medium-, long-range).
Numerical Weather Prediction (NWP) familiarity — configuration, tuning, and verification of models such as WRF, GFS, HRRR, ICON.
Ensemble forecasting and probabilistic methods (ensembles, MOS, BMA).
Data assimilation concepts and operational DA systems (3DVar, 4DVar, EnKF) and experience working with analysis cycles.
Radar and satellite remote sensing interpretation (Doppler radar, SAR, GOES/GEO, polar-orbiting sensors).
Programming and scripting: Python (xarray, pandas, MetPy), Fortran (legacy model code), Bash — ability to automate operational workflows.
Cloud and infrastructure: AWS/GCP experience for model runs, data storage, and scalable processing (EC2, S3, Kubernetes).
Database and data engineering basics: SQL, time-series databases, data pipelines (Airflow, Kafka).
Machine learning/statistical post-processing for forecasts: scikit-learn, TensorFlow/PyTorch, probabilistic calibration methods.
GIS and spatial analysis: ArcGIS, QGIS, spatial libraries (GeoPandas, rasterio) for impact mapping and product generation.
Instrumentation and sensor management: radars, profilers, automatic weather stations (AWS), calibration and maintenance procedures.
Verification, performance metrics, and forecast evaluation frameworks (CRPS, Brier score, ROC, POD, FAR).
API design and productization of meteorological data (RESTful APIs, JSON schemas, documentation).
DevOps/CI-CD familiarity for operational release management and automated model/post-processing deployments (Docker, GitLab CI, Jenkins).
Knowledge of national weather services, regulatory frameworks, and emergency management protocols (ICS, EAS/SAME).

Soft Skills

Strong leadership and people management with experience coaching operational teams under high-pressure conditions.
Excellent verbal and written communication for technical briefings, public alerts, and executive updates.
Decision-making under uncertainty, prioritizing safety and operational impact in fast-moving weather situations.
Stakeholder management: ability to build trust with internal customers, government agencies, and commercial partners.
Collaborative mindset with experience running cross-functional initiatives and translating science into business outcomes.
Problem-solving and continuous-improvement orientation, applying verification insights to operational change.
Project management skills, including budgeting, vendor negotiation, and roadmap delivery.
Customer empathy and training capability to ensure forecast products meet end-user decision support needs.
Adaptability to evolving technologies and a growth mindset toward research-to-operations (R2O) transitions.
Attention to documentation, reproducibility, and data governance to support audits and model traceability.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Meteorology, Atmospheric Science, Climatology, Environmental Science, or a closely related scientific field.

Preferred Education:

Master's degree or PhD in Meteorology, Atmospheric Science, Data Science with atmospheric focus, or related discipline preferred for senior or research-focused roles.

Relevant Fields of Study:

Meteorology / Atmospheric Science
Climatology / Climate Science
Environmental Science / Hydrometeorology
Data Science / Statistics (with atmospheric applications)
Computer Science / Engineering (for operational modeling and infrastructure)

Experience Requirements

Typical Experience Range:

5 — 10+ years in operational meteorology, forecasting centers, weather product management, or applied atmospheric research with operational deployments.

Preferred:

7+ years of progressive responsibility including team leadership, hands-on forecasting experience (including severe-weather operations), operational model deployment, verification program ownership, and vendor/partner management. Experience in a 24/7 operational environment, emergency management coordination (ICS), and product commercialization is highly desirable.