Lowest temperature in Oklahoma City on Jun 25, 2026?

Prediction market odds reflect aggregated trader expectations and often diverge from traditional meteorological forecasts. While weather analysts issue point estimates and confidence intervals based on numerical models, this market prices uncertainty through continuous trading, allowing participants to express nuanced views on tail risks and model disagreement. Comparing the implied probability of extreme cold snaps in this market to published seasonal outlooks can reveal whether traders are pricing in more or less downside risk than official forecasters, offering a complementary perspective on June temperature expectations.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to specific temperature ranges. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome contract represents a discrete low-temperature bracket, and the price of each contract reflects the collective probability assigned by active traders. As new weather data emerges or seasonal patterns shift, traders adjust their positions, causing prices to move in real time and creating a dynamic market price that synthesizes available information.

This market resolves around Jun 26, 2026, once June 25, 2026 has passed and the lowest temperature recorded in Oklahoma City that day is confirmed. The outcome is determined by verified meteorological data from credible public sources, ensuring an objective and transparent settlement. Traders holding contracts aligned with the actual low temperature receive their payout, while misaligned positions expire worthless.

Major shifts in seasonal climate forecasts, updates to long-range weather models, and historical temperature anomalies for late June in Oklahoma can drive significant price swings. El Niño or La Niña developments, upper-atmosphere pattern changes, and tropical activity affecting North American weather systems are key catalysts. As June 2026 approaches, weekly and daily forecasts will become increasingly precise, typically triggering sharp repricing. Unusual heat waves or cold fronts in preceding months may also reset trader expectations for the specific low-temperature outcome.