Meteomatics Professional Weather Data API
Meteomatics professional weather data REST API for energy companies, airlines, logistics, agriculture, and financial institutions to access high-resolution numerical weather prediction (NWP) data, climate data, and historical weather through a URL-based query interface supporting global grid and point data in multiple formats (JSON, CSV, NetCDF, PNG), covering 1,000+ weather parameters with ensemble forecasts, reanalysis data, and proprietary Meteomatics Mix model output. Enables AI agents to manage weather forecast retrieval for precision weather data automation, handle historical reanalysis for climate and backtest automation, access ensemble forecast for probabilistic weather automation, retrieve aviation METAR/TAF equivalent for flight operation weather automation, manage energy production forecast for renewable energy optimization automation, handle agricultural weather for crop and irrigation automation, access marine weather for maritime route optimization automation, retrieve climate model data for long-range planning automation, manage weather grid data for GIS and mapping automation, and integrate Meteomatics with energy trading, logistics, aviation, and agricultural intelligence platforms for end-to-end professional weather data automation.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Professional meteorological data. GDPR, ISO 9001. Basic auth. EU. Weather model data only.
⚡ Reliability
Best When
An energy company, airline, logistics firm, or agricultural platform wanting AI agents to access high-resolution numerical weather prediction, ensemble forecasts, and climate reanalysis through Meteomatics' professional meteorological data platform.
Avoid When
URL-BASED QUERY SYNTAX IS PROPRIETARY: Meteomatics uses a custom URL path format (date/parameters/location/format) not standard REST JSON body; automated query must construct proper Meteomatics URL syntax; automated standard REST JSON body request creates malformed query. HIGH-RESOLUTION DATA IS LARGE: Meteomatics grid data (e.g., 0.1° global) can be very large; automated grid query without bounding box creates GB-scale response; automated must specify appropriate spatial resolution and bounding box. ENSEMBLE FORECAST REQUIRES MEMBER SPECIFICATION: Meteomatics ensemble data requires specifying number of ensemble members; automated deterministic forecast assumption creates single-member response without uncertainty; automated probabilistic forecast must request ensemble members. CREDIT-BASED PRICING DEPLETES QUICKLY: Meteomatics API is credit-based per data point; automated high-resolution global grid query depletes credits rapidly; automated must implement data point budgeting per query.
Use Cases
- • Accessing high-resolution NWP data for renewable energy production forecasting automation agents
- • Retrieving ensemble weather forecasts for agricultural crop planning automation agents
- • Querying aviation weather parameters for flight dispatch and route optimization agents
- • Analyzing historical reanalysis data for climate risk and financial hedging automation agents
Not For
- • Consumer weather display (use OpenWeatherMap or WeatherAPI for consumer-grade data)
- • Real-time severe weather alerts for mass notification (use commercial alert services)
- • Simple current conditions lookup (Meteomatics is professional/enterprise grade, costs more)
Interface
Authentication
Meteomatics uses HTTP Basic Auth (username/password) for API authentication. URL-based query format. St. Gallen, Switzerland HQ. Founded 2012 by Martin Fengler. Bootstrapped to profitability. Products: NWP data, ensemble forecasts, climate reanalysis, aviation weather, energy forecasting. SDKs: Python, R, MATLAB. ISO 9001. WMO member. Serves energy, aviation, logistics, agriculture, finance. Competes with IBM Weather (The Weather Company) and DTN for professional weather data.
Pricing
St. Gallen CH. Bootstrapped. Credit/data-point pricing model. CHF pricing. ISO 9001. WMO member.
Agent Metadata
Known Gotchas
- ⚠ PROPRIETARY URL PATH SYNTAX: Meteomatics query format is a custom URL path (not JSON body): /validDateTime/parameters/location/format; automated standard REST JSON request creates 400 malformed query; automated must construct correct URL path format with correct date, parameter, and coordinate encoding
- ⚠ CREDIT CONSUMPTION BY DATA POINTS: Meteomatics charges credits per requested data point (parameter × location × time); automated broad grid query consumes massive credits unexpectedly; automated must estimate credit cost before executing high-resolution queries
- ⚠ BASIC AUTH WITH USERNAME/PASSWORD: Meteomatics uses HTTP Basic Authentication (not API key or OAuth); automated API key header assumption creates 401 unauthorized; automated must use Authorization: Basic base64(username:password) header
- ⚠ ENSEMBLE MEMBER SELECTION REQUIRED: Meteomatics ensemble data requires specifying ensemble member count or individual members; automated deterministic-only assumption misses probabilistic forecast capability; automated ensemble must specify member parameter in URL
- ⚠ LARGE GRID RESPONSES REQUIRE STREAMING: Meteomatics NetCDF or high-resolution grid responses can be hundreds of MB; automated in-memory response assumption for large grids creates OOM; automated grid queries must stream response to file
Alternatives
Full Evaluation Report
Comprehensive deep-dive: security analysis, reliability audit, agent experience review, cost modeling, competitive positioning, and improvement roadmap for Meteomatics Professional Weather Data API.
AI-powered analysis · PDF + markdown · Delivered within 30 minutes
Package Brief
Quick verdict, integration guide, cost projections, gotchas with workarounds, and alternatives comparison.
Delivered within 10 minutes
Score Monitoring
Get alerted when this package's AF, security, or reliability scores change significantly. Stay ahead of regressions.
Continuous monitoring
Scores are editorial opinions as of 2026-03-07.