Question: I need a weather service that provides sub-hourly forecasts and short-term smoke forecasts for my application.

If you want a weather service that offers sub-hourly forecasts and short-term smoke forecasts, Pirate Weather is a great option. This service offers raw model data from government agencies like NOAA with little processing, so you can see exactly how forecasts are made. It supports multiple model sources, including NBM, HRRR, GFS, and ERA5, and offers sub-hourly forecasts and short-term smoke forecasts. With options like fire index, precipitation types, and nearest storm distance and bearing, Pirate Weather is great for people who need more detailed weather information.

Another option is Atmo, an AI-powered weather forecasting system that consumes data from a wide range of sources and uses deep learning models to refine forecasts over time. Atmo offers hyper-local weather forecasting with up to 50% more accuracy than traditional forecasts, making it great for applications that need detailed, granular weather information. It can generate forecasts up to 40,000 times faster than traditional models, so you can get the information you need in a timely manner.

If you're looking for a more comprehensive weather resilience platform, check out Tomorrow.io. This platform offers hyper-accurate weather data and forecasts, real-time weather data, and APIs for up to 14 days of forecasting. Tomorrow.io also offers features like probabilistic forecasting and generative AI for personalized recommendations. It's designed to help businesses manage weather risks and build long-term resilience, so it's great for companies that need detailed and reliable weather data.

Last, Rainbow offers hyperlocal weather updates with 1-minute temporal resolution and 1 sq km spatial resolution. It's geared for businesses that need hyperlocal weather data for decision-making, such as ridesharing, same-day delivery, and solar energy. Rainbow offers a variety of API plans, including a pay-as-you-go option, so it can accommodate different user needs.