Atmospheric G2 provides precise weather forecasts, including wind and solar generation predictions, degree days, and natural gas usage metrics, utilizing advanced probabilistic data analytics and APIs for seamless integration. The company enables energy traders and businesses to make informed decisions by delivering real-time, high-resolution weather data that directly impacts energy market dynamics.
Funding
Funding not disclosed
Founders
Product
Problem
Energy traders and businesses require accurate weather forecasts to make informed decisions, but traditional weather data often lacks the precision and specific metrics needed for energy market dynamics. Existing solutions may not adequately translate weather data into actionable insights like wind/solar generation predictions, degree days, and natural gas usage forecasts.
Solution
Atmospheric G2 (AG2) provides weather and climate intelligence, delivering precise weather forecasts and historical data tailored for the energy sector. AG2 converts raw weather data into actionable metrics, including wind and solar generation forecasts, degree days, and natural gas usage forecasts (in Bcf). The company's FRisk index and probabilistic data analytics help clients evaluate weather forecast risk, enabling optimal business decisions. AG2 offers a Trader graphical interface and a suite of APIs, allowing users to integrate data into existing models for energy trading, asset management, weather derivative trading, and insurance/reinsurance.
Target Audience
The primary users are energy traders, asset managers, and businesses involved in weather derivative trading and insurance/reinsurance.
Features
- High-resolution global GRAF model and IBM temperature forecast stream via partnership with The Weather Company
- FRisk index and associated probabilistic data stream for evaluating weather forecast risk
- Customizable Trader interface displaying 15-day forecasts at daily or hourly resolution
- Hourly data updates for cities and regions in North America, Europe, Asia, and Australia
- AI/ML techniques for load (energy demand) forecasts for various US power pools
- APIs for integrating weather data into existing scripts and models