Lowest temperature in Dallas on Jun 21, 2026?

Prediction market odds reflect real-money incentives for accuracy, often incorporating meteorological models and historical climate patterns faster than traditional analyst consensus. While weather forecasters issue deterministic point estimates or ranges, this market aggregates the beliefs of many traders with financial skin in the game. The odds can diverge from official forecasts when new data emerges or when market participants anticipate systematic bias in conventional models. Comparing the two reveals whether traders are pricing in tail risks or seasonal anomalies that analysts may underweight.

On Kalshi, this market is priced through a continuous order-book mechanism where traders submit bids and offers for shares corresponding to different temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each outcome reflects the marginal probability assigned by the last matched trade, and spreads tighten as volume increases and more participants compete. Prices update in real time as new weather forecasts, historical data, or seasonal trends influence trader conviction, allowing you to enter or exit positions at transparent, market-determined rates.

This market resolves around Jun 22, 2026, once June 21, 2026 has passed and the lowest temperature recorded in Dallas that day is verifiable from credible public sources. The outcome is determined by comparing actual meteorological data to the temperature thresholds defined in the market's outcome categories. Your position settles based on which range the verified low temperature falls into, with payouts distributed accordingly to holders of the correct outcome share.

Major weather pattern shifts, updated seasonal climate outlooks, and long-range forecast model revisions can significantly move odds in this market. El Niño or La Niña conditions, jet stream positioning, and historical analogues to past June 21 temperatures in Dallas all influence trader expectations. As the event date approaches, short-range forecasts become more precise and volatile, often triggering sharp repricing. Real-time atmospheric data releases and any unusual heat or cold anomalies in the weeks leading up to June 2026 will likely drive the most dramatic swings.