Lowest temperature in San Francisco on Jun 19, 2026?

Prediction market odds often diverge from traditional weather forecasts because they incorporate real-time trader behavior, risk appetite, and emerging data. While meteorologists rely on physics-based models and historical patterns, this market aggregates the beliefs of many participants with financial incentives to forecast accurately. Comparing the implied probabilities here to official forecasts from the National Weather Service or other agencies can reveal where the crowd sees asymmetric risk—for instance, if traders price in a higher chance of extreme cold than models suggest, or vice versa.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to different temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome has a price between 0 and 100 cents, reflecting the implied probability that the lowest temperature will fall within that range. As traders place bids and offers, prices adjust in real time, and the spread between buy and sell prices narrows or widens based on demand and available liquidity.

This market resolves around Jun 20, 2026, after June 19, 2026 concludes. The outcome is determined by the verified lowest temperature recorded in San Francisco on that date, confirmed once the event is observable from credible public reporting. Traders holding shares in the correct outcome receive their payout once the temperature is finalized and the market settles.

Several factors may shift odds in this market: updated seasonal forecasts, El Niño or La Niña patterns, atmospheric pressure systems, and historical temperature anomalies for mid-June in the Bay Area. Major weather model updates—especially from the National Weather Service or European Centre for Medium-Range Weather Forecasts—often trigger repricing. Additionally, unusual climate events or volcanic activity affecting solar radiation could influence long-term temperature expectations. As June 19 approaches, short-term forecasts become more precise, typically tightening the range of likely outcomes and reducing uncertainty.