Lowest temperature in Chicago on Jun 24, 2026?

Prediction market odds often diverge from traditional meteorological forecasts because traders incorporate real-time data, historical patterns, and their own risk assessments into prices. While weather analysts publish deterministic point forecasts or confidence intervals, this market aggregates the collective judgment of many participants betting real money on outcomes. Comparing the leading odds here to published forecasts from the National Weather Service or private meteorology firms can reveal where the crowd sees upside or downside risk relative to expert consensus, though both sources draw from the same underlying atmospheric models and observational data.

On Kalshi, this market is priced through an order-book mechanism where traders submit bids and asks for each temperature outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices reflect the marginal probability that traders assign to each bracket, with tighter spreads indicating higher confidence and wider spreads suggesting uncertainty. As new information emerges—weather model updates, seasonal patterns, or real-time atmospheric changes—traders adjust their orders, causing prices to shift. The platform's matching engine executes trades continuously, ensuring that the displayed odds always represent the most recent consensus among active participants.

This market resolves around Jun 25, 2026, once June 24, 2026 has passed and the day's weather data is finalized. The outcome is determined by the lowest temperature recorded in Chicago on that date, verified against credible public sources such as the National Weather Service or established meteorological databases. Traders holding positions in the correct temperature bracket at resolution receive their payout, while incorrect positions expire worthless. The resolution process is automatic once the official low temperature is confirmed and published.

Major weather model updates, seasonal climate anomalies, and long-range forecast revisions will drive significant price swings in this market. El Niño or La Niña patterns, Arctic air outbreaks, or unusual jet-stream positioning could shift expectations for June temperatures substantially. As the event date approaches, medium-range forecasts become more reliable, typically causing volatility to spike when new data arrives. Additionally, historical June temperature records for Chicago and any emerging climate trends will influence trader positioning. Real-time atmospheric monitoring and model consensus shifts in the final weeks before June 24 will be the primary catalysts for price movement.