If you're looking for high-resolution weather forecasts that are useful for government or business purposes, you might want to take a look at Atmo. This AI-based system collects data from a variety of sources, including satellites, ground stations and radar, to generate hyperlocal forecasts that are up to 50% more accurate than conventional models. It's geared for small models, down to 1km by 1km, that can capture nano-climate details and update at lightning speed for the most precise predictions.
Another good option is Tomorrow.io, a weather resilience platform that includes hyper-accurate forecasts, real-time data and weather APIs that span 14 days of forecast and 20 years of historical data. The platform includes features like probabilistic forecasting, generative AI for personalized recommendations, and automated protocols that can be useful for businesses that need to monitor and respond to weather risks.
If you need hyperlocal weather data for specific purposes, Rainbow is worth a look. This AI-based app and API can provide 1-minute temporal resolution and 1 sq km spatial resolution for any location. It's geared for businesses like aviation, agriculture and solar power that need minute-by-minute and precise weather forecasts.
If you prefer a more integrated weather data approach, Weather Machine combines data from sources like AccuWeather and The Weather Company into a single interface. It's geared for developers and businesses, with features like forecast-aware caching and multiple data retrieval options, so you can more easily build weather data into your apps.