Lowest temperature in Chicago on Jun 25, 2026?

Prediction market odds reflect aggregated trader beliefs and often diverge from traditional meteorological forecasts because markets price in uncertainty and real-time data updates. While weather analysts publish deterministic point forecasts or confidence intervals weeks in advance, this market continuously reprices as new atmospheric data arrives and the event date approaches. Comparing the implied probabilities here to published seasonal or extended-range forecasts can reveal where professional meteorologists and market participants agree or disagree on temperature likelihood.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to different temperature ranges. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome bracket has its own bid-ask spread, and the current mid-price reflects the marginal trader's willingness to accept that temperature threshold. As new information emerges—updated climate models, historical analogs, or seasonal patterns—traders adjust their positions, moving prices to equilibrate supply and demand across all possible low-temperature outcomes.

This market resolves around Jun 26, 2026, once June 25, 2026 has passed and the actual lowest temperature in Chicago can be verified from credible public sources. The outcome is determined by the recorded minimum temperature on that date, measured and reported by official weather stations serving the Chicago area. Traders holding shares in the correct outcome bracket receive their payout once the final temperature is confirmed and the market settles.

Major atmospheric pattern shifts, updated seasonal climate outlooks, and historical temperature anomalies for late June can all drive significant repricing. El Niño or La Niña transitions, polar vortex behavior, and jet-stream positioning influence summer temperatures in the Midwest. Additionally, as June 2026 approaches, real-time weather models become more precise, allowing traders to refine their bets. Extreme heat waves or cold snaps in preceding weeks may also shift expectations about what constitutes a typical low for that date.