Lowest temperature in Atlanta on Jun 21, 2026?

Prediction market odds reflect real-money bets from traders who research weather patterns, historical climate data, and meteorological models. Unlike traditional analyst forecasts, which rely on expert opinion and statistical models alone, this market aggregates dispersed information through price discovery. Traders who accurately predict the low temperature profit, creating a financial incentive for accuracy. Over time, prediction markets often converge toward outcomes that outperform single-source forecasts, though both approaches have merit for understanding likely temperature ranges.

On Kalshi, this market is priced through an order-book mechanism where buyers and sellers submit bids and offers for different temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Traders compete to buy low and sell high, and the market price at any moment reflects the consensus probability of each outcome. Prices typically range from near zero to near 100, with higher prices indicating stronger trader conviction that a particular temperature range will occur. Liquidity and trading volume influence how tightly prices cluster around fair value.

This market resolves around Jun 22, 2026, once June 21, 2026 has passed and the lowest temperature recorded in Atlanta that day is verified. The outcome is confirmed against credible public sources that document official weather data. Traders holding positions on the correct temperature range at resolution receive their payout, while incorrect positions expire worthless. The resolution process is automated once the data becomes available, ensuring all traders receive results simultaneously.

Major weather pattern shifts, seasonal climate anomalies, and updated long-range forecasts from meteorological agencies can significantly move this market. El Niño or La Niña conditions, atmospheric pressure systems, and historical temperature records for mid-June in Atlanta all influence trader expectations. As the event date approaches, short-range forecasts become more reliable and typically trigger sharper price moves. Breaking news about unusual climate events or revised seasonal outlooks may also prompt rapid repricing as traders adjust their positions based on new information.