Lowest temperature in San Francisco on Jun 24, 2026?

Prediction market odds reflect real-money commitments from traders and often diverge from traditional weather forecasts or analyst estimates. While meteorologists issue point forecasts or confidence intervals based on atmospheric models, this market aggregates the collective judgment of participants who have financial incentive to be accurate. Comparing the implied probability in this market to published forecasts from the National Weather Service or other agencies can reveal where traders see greater or lower risk than official models suggest. Such divergences sometimes highlight uncertainty that conventional forecasts may underweight.

On Kalshi, this market is priced through a continuous 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 share represents a claim on a specific temperature range or threshold, and the market price reflects the current balance of buy and sell orders. As new weather data, seasonal patterns, or climate signals emerge, traders adjust their positions, moving the odds up or down. The platform's matching engine ensures transparent price discovery and allows participants to enter or exit positions at any time before the market closes.

This market resolves around Jun 25, 2026, once June 24, 2026 has passed and the day's minimum temperature can be verified from credible public sources. The outcome is determined by the lowest temperature recorded in San Francisco on that date, confirmed through official weather reporting. Traders' positions settle based on whether the actual low falls within the range they backed. Resolution occurs shortly after the event is finalized and reported by authoritative weather data providers.

Several factors could shift odds in this market before June 2026. Long-range climate forecasts, El Niño or La Niña patterns, and seasonal anomalies may influence trader expectations about summer temperatures in the Bay Area. Major weather events or atmospheric circulation changes in the months leading up to June could alter the probability distribution. Additionally, updated climate models or historical temperature comparisons to previous June 24ths might prompt traders to reassess their positions. Real-time weather developments closer to the event date will likely drive the most significant price movements.