Key Responsibilities and Required Skills for Weather Intern

🎯 Role Definition

This role requires a proactive Weather Intern to support forecasting operations, field campaigns, data ingestion and quality-control workflows, and meteorological research. The Weather Intern will work alongside operational meteorologists, research scientists and data engineers to collect and clean observational data, run and evaluate NWP output, prepare visualizations for stakeholders, and contribute to weather briefings and model verification. This is a high-impact internship designed to build practical forecasting, remote sensing and data analysis skills while contributing to real-world weather services and research.

📈 Career Progression

Typical Career Path

Entry Point From:

Undergraduate student in Meteorology, Atmospheric Science, Environmental Science, or related STEM field.
Recent graduate seeking applied meteorology experience.
Field technician or volunteer with observational campaign experience.

Advancement To:

Weather Technician / Forecast Technician
Operational Meteorologist / Forecast Analyst
Meteorological Data Analyst or NWP Modeler
Climate Analyst or Research Scientist

Lateral Moves:

GIS Analyst (with a focus on weather/climate data)
Environmental Scientist / Hydrometeorologist

Core Responsibilities

Primary Functions

Assist operational forecasters by monitoring real-time atmospheric observations (surface stations, upper-air soundings, radar, satellite) and flagging anomalous or hazardous conditions to supervisors and the forecasting team.
Collect, calibrate and maintain routine observational instruments (automatic weather stations, anemometers, temperature/humidity sensors, solar radiation sensors), perform routine maintenance checks, and log instrument performance and repairs.
Prepare and quality-control ingestion pipelines for observational datasets (METAR, SYNOP, buoy, radiosonde, profiler and GNSS-RO), documenting metadata and flagging missing or suspect values for downstream analysis.
Run, post-process and verify short-range NWP model output (e.g., WRF, GFS, NAM), generate bias-corrected forecasts and produce model comparison summaries for internal briefings and model development teams.
Support field campaign logistics including radiosonde launches, surface station deployments, mobile observations, and documentation of field sampling protocols and chain-of-custody for collected data.
Analyze radar and satellite imagery to identify convective initiation, storm evolution, precipitation type and intensity, and produce annotated imagery and short written briefings for forecasters and partners.
Create reproducible data processing workflows in Python, R or MATLAB for ingesting raw observational/model data, performing quality control, computing derived variables, and exporting standardized datasets for analysis.
Develop and maintain automated visualization dashboards (using Python, Jupyter, Plotly, Grafana or Tableau) that show real-time and archived meteorological variables, model guidance and verification metrics for internal and external users.
Perform statistical model verification and forecast skill assessments using deterministic and probabilistic metrics (RMSE, MAE, Brier Score, CRPS), summarize results in clear written reports and recommend improvements for operational use.
Assist in the development and testing of new forecast products and user-facing weather services (e.g., probabilistic precipitation maps, heat stress indices, aviation briefings) by generating prototypes and collecting stakeholder feedback.
Process and interpret remote sensing data (GOES/Himawari/Meteosat infrared and visible channels, microwave sounders, scatterometer and passive microwave products) to support situational awareness and short-term forecasting needs.
Support hydrometeorological tasks such as precipitation accumulation monitoring, snowpack observations, and river/stream gauge trend analysis for flood risk monitoring and warning support.
Perform geospatial analyses of meteorological datasets using GIS (ArcGIS/QGIS) to create maps of exposure, vulnerability or model output overlays for emergency management and planning teams.
Document standard operating procedures (SOPs), data dictionaries and runbooks for routine tasks to ensure reproducibility, knowledge transfer and continued operations during staff rotations.
Collaborate with cross-functional teams (research scientists, data engineers, software developers) to help integrate new observational networks or model output into operational systems, testing ingestion and transformation pipelines.
Assist with socialization of weather information by drafting short, actionable weather summaries, briefing slides, and social-media ready content for internal distribution and external stakeholders.
Participate in regular forecast briefings, shift handovers and debriefs, contributing insights from data analyses, model evaluation and field observations to improve forecast accuracy and communication.
Conduct literature reviews and small research projects to evaluate new observational techniques, model configurations or verification methods, and present findings to the scientific or operations team.
Support quality assurance and metadata compliance for archived datasets to meet agency or institutional data-sharing policies (e.g., NOAA, WMO standards), and assist in preparing data packages for public release.
Troubleshoot common software and data pipeline issues in a Linux environment, manage scheduled jobs, and escalate complex outages to system administrators with clear incident reports.
Assist with outreach and educational initiatives such as campus weather seminars, K-12 engagement events or partner training sessions to communicate basic meteorological concepts and internship outcomes.

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.
Support creation of documentation and training materials for operational tools and dashboards.
Help evaluate vendor datasets, APIs and third-party model products for potential integration.

Required Skills & Competencies

Hard Skills (Technical)

Working knowledge of meteorological observation systems and ability to interpret METAR, SYNOP, ICAO and surface station reports.
Familiarity with numerical weather prediction models and model output formats (e.g., GRIB, NetCDF), and basic experience running or post-processing WRF/GFS/NAM output.
Proficient in Python for data analysis (pandas, xarray, numpy) and visualization (matplotlib, Cartopy, Plotly) with reproducible Jupyter notebooks.
Experience with data quality control tools and procedures for observational and model datasets.
Basic GIS skills with ArcGIS or QGIS for mapping meteorological information and spatial analyses.
Experience reading and interpreting satellite and radar products (GOES, Himawari, NEXRAD) and derived remote sensing products.
Familiarity with Linux/Unix command line, cron jobs and basic shell scripting for automating routine tasks.
Experience with SQL for querying meteorological databases and working with relational data stores.
Knowledge of model verification techniques and forecast evaluation metrics (RMSE, Brier Score, CRPS, POD, FAR).
Exposure to cloud services (AWS/GCP) for data storage and processing, including S3 and cloud compute basics.
Basic understanding of atmospheric dynamics and thermodynamics relevant to forecasting (fronts, instability, moisture transport).
Experience with version control (git) and collaborative code repositories (GitHub, GitLab).

Soft Skills

Clear written and verbal communication skills for technical documentation and briefing stakeholders.
Ability to work collaboratively in interdisciplinary teams and adapt to rotating shift schedules.
Strong problem-solving mindset with attention to detail and data hygiene.
Time management and ability to prioritize tasks during busy weather events or field deployments.
Curiosity and continuous-learning attitude toward new tools, models and observational techniques.
Ability to present technical information to non-technical audiences and produce concise executive summaries.
Professionalism in fieldwork settings and adherence to safety protocols during deployments.
Initiative to identify process improvements and propose practical solutions.
Resilience under time pressure and capacity to perform in operational environments with strict SLA expectations.
Ethical handling of observational data and adherence to data privacy and licensing requirements.

Education & Experience

Educational Background

Minimum Education:

Currently enrolled in or recently completed a Bachelor's degree in Meteorology, Atmospheric Science, Environmental Science, Climate Science, Physics, or related STEM discipline.

Preferred Education:

Pursuing or completed a Bachelor’s or Master’s degree with coursework in synoptic meteorology, atmospheric dynamics, remote sensing, or numerical modeling.

Relevant Fields of Study:

Meteorology / Atmospheric Science
Environmental Science / Hydrology
Climate Science / Geosciences
Physics / Applied Mathematics
Computer Science or Data Science (with meteorology electives)

Experience Requirements

Typical Experience Range:

0 to 2 years (internship/academic projects/field campaign experience acceptable)

Preferred:

Prior internship, research assistantship, or volunteer work involving observational networks, model post-processing, radar/satellite interpretation or field deployments.
Experience working with NWP output, Python-based data workflows, and basic GIS mapping.
Demonstrated coursework or project experience in meteorological data analysis and model evaluation.