Lowest temperature in Oklahoma City on Jun 28, 2026?

Prediction market odds reflect real-money trader conviction and aggregate information across many participants, often incorporating meteorological models, historical climate data, and seasonal trends that professional forecasters also use. While weather analysts publish point estimates and confidence intervals based on numerical models, this market prices uncertainty through continuous trading. The two approaches can diverge when traders weigh emerging atmospheric patterns differently than published forecasts, or when new data shifts market sentiment faster than traditional forecast updates. Comparing the two reveals where market participants see value relative to expert consensus.

On Kalshi, this market is priced through an order-book mechanism where traders submit bids and asks for shares tied to specific temperature ranges or 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 supply and demand; as more traders expect a particular low temperature, the corresponding shares rise in value. Your position's value updates continuously as the market reprices based on new trades and information. Settlement occurs after the event, with payouts determined by which outcome bracket the actual temperature falls into.

This market resolves around Jun 29, 2026, once the lowest temperature recorded in Oklahoma City on June 28, 2026 is verified and confirmed. The outcome is determined by comparing the actual low temperature against the predefined outcome brackets established at market creation. Your position settles based on which bracket the verified temperature falls into, with payouts distributed accordingly. Resolution relies on credible public temperature data from established weather monitoring sources.

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, Arctic oscillation changes, and historical temperature records for late June in Oklahoma City all influence trader positioning. As June 2026 approaches, short-range weather models become more reliable and often trigger sharp repricing. Breaking news about climate events, atmospheric blocking patterns, or heat waves in adjacent regions may also shift expectations, causing traders to adjust their bids and offers in response to new information.