Whether you're training a machine learning model, building a multi-agent simulation, or developing an AI-powered app that needs real-world context, historical weather data can add serious value to your project.

The good news? You don't need to pay for it. Many APIs offer free or open access to weather history. Some provide global coverage, others specialize in granular hourly data. In this post, I'll walk you through 9 weather APIs you can use for free — perfect for AI and data-driven applications.

1. 🌤 Open-Meteo (No API Key Needed)

Best for: Fast access to free historical weather — no strings attached.

  • ✅ Free and open-source
  • ❌ No API key required
  • 🌍 Global coverage
  • 📊 JSON output format
  • 📅 Supports time-specific queries

Example:

https://archive-api.open-meteo.com/v1/archive?latitude=52.52&longitude=13.41&start_date=2022-01-01&end_date=2022-01-01&hourly=temperature_2m

🔗 Docs

2. 📊 Meteostat

Best for: Long-term historical data with Python integration.

  • ✅ Up to 10+ years of hourly and daily data
  • 🐍 Great Python library support
  • ⚠️ API key only needed for high-volume usage

Python example:

from meteostat import Point, Hourly
from datetime import datetime

location = Point(52.52, 13.41)  # Berlin
start = datetime(2022, 1, 1)
end = datetime(2022, 1, 2)

data = Hourly(location, start, end)
df = data.fetch()
print(df)

🔗 Docs

3. 🌦 Visual Crossing

Best for: Rich, detailed data in a developer-friendly format.

  • ✅ Forecast + historical data
  • ✅ Generous free tier
  • 🔑 Requires API key
  • 🛰 Offers cloud cover, conditions, wind speed, etc.

Example:

https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/London/2022-01-01?unitGroup=metric&key=YOUR_API_KEY

🔗 Docs

4. ☁️ WeatherAPI.com

Best for: Simple historical queries for recent data (last 7 days).

  • ✅ Free tier for recent data
  • 🔑 API key required
  • 📋 Data includes temperature, humidity, wind, and condition

Example:

https://api.weatherapi.com/v1/history.json?key=YOUR_API_KEY&q=London&dt=2022-01-01

🔗 Docs

5. 🌐 Tomorrow.io (formerly ClimaCell)

Best for: AI-ready, structured weather insights with advanced features.

  • ✅ Up to 1 year of historical data on free plan
  • 🔑 API key required
  • 🧠 Ideal for ML models needing highly structured data

🔗 Docs

6. 📈 Weatherstack

Best for: Lightweight historical data for quick lookups.

  • ✅ Free tier includes historical weather
  • 🔑 API key required
  • 📦 JSON-based responses, easy to integrate

🔗 Docs

7. 🌍 World Weather Online

Best for: Up to 60 days of recent historical data.

  • ✅ Free tier allows past 60-day access
  • 🔑 API key required
  • 🌐 Supports city name, coordinates, or IP-based queries

🔗 Docs

8. 🌡 OpenWeatherMap

Best for: Weather data with hourly resolution and SDK support.

  • ✅ Free tier allows up to 1 month of history
  • 🔑 API key required
  • 📦 Has SDKs for Python, JavaScript, and more

Example:

https://history.openweathermap.org/data/2.5/history/city?q=London&type=hour&start=1609459200&end=1609545600&appid=YOUR_API_KEY

🔗 Docs

9. ☀️ NASA POWER API

Best for: Scientific-grade satellite weather and climate data.

  • ✅ Completely free and open-access
  • ❌ No API key required
  • 🌐 Global coverage
  • 📊 Includes solar radiation, humidity, temperature, and more

🔗 Docs

📝 Summary Table:

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🧠 Final Thoughts

Whether you're working on climate simulations, agricultural AI tools, smart cities, or energy optimization models, adding historical weather data can significantly boost model performance and realism.

  • Want zero hassle? Start with Open-Meteo or NASA POWER.
  • Need long-term or detailed weather data? Try Meteostat or Visual Crossing.
  • Looking for a developer-friendly API with great docs? Consider WeatherAPI or Tomorrow.io.