FAQ
Atmospheric G2 Frequently Asked Questions
Atmospheric G2 provides operational weather intelligence and decision support for organizations where weather impacts safety, reliability, and cost.
Can you provide weather data for energy trading?
Yes. Atmospheric G2 is a cornerstone of energy and financial industries due to:
25+ years of experience
Hundreds of energy and market-focused customers
Used daily in energy trading and risk management workflows
Where does the company name Atmospheric G2 come from?
Atmospheric (adjective) – generally, relating to the atmosphere of the earth; specifically, for our purposes, relating to weather and climate. G2 (noun) – In-depth information about any person or thing; an intelligence report.
We started out as WSI in 2000 but the name Atmospheric G2 (or AG2) has been in use since 2021.
How long have you been in business?
The AG2 Trader (WSI Trader) platform has driven weather-based energy commodity markets for more than 25 years. The company started as WSI and has evolved under various ownership groups to where it has landed today, with a small, laser-focused mission to provide the fastest, most accurate, and most insightful weather platform in the world.
Why is AG2 unique and better placed to serve customers than others?
Atmospheric G2 combines forecast accuracy, deep domain expertise, and decision-focused innovation in a way few weather intelligence providers can match.
We deliver industry-leading 15-day and seasonal forecasts, trusted by energy and market-focused organizations that depend on precision and reliability. Unlike newer entrants, many of our senior team members have been building Atmospheric G2 since its inception as WSI, giving us long-standing insight into how weather impacts real-world trading, operations, and risk management.
Our growing team of experienced meteorologists includes professionals with direct trading-floor and market experience, enabling us to translate atmospheric science into actionable, decision-ready intelligence. We further differentiate ourselves through proprietary models and analytics—such as FRisk and Probabalisitic, and the GRAF model—that help customers quantify forecast risk and make more confident business decisions.
























