Lowest temperature in San Francisco on Jun 29, 2026?

Prediction market odds often diverge from traditional weather analyst forecasts because they incorporate real-time trader positioning and incentivize accuracy through financial stakes. While meteorologists issue probabilistic forecasts based on atmospheric models, this market prices outcomes dynamically as new data emerges and traders update their views. Over time, prediction markets have proven competitive with or superior to expert consensus on weather events, since participants with strong forecasting ability profit by correcting mispriced odds. Comparing the current odds here to published forecasts from the National Weather Service or similar agencies can reveal where the crowd sees edge.

On Kalshi, this market is priced through a continuous order book where traders buy and sell shares corresponding to specific temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome contract trades independently, and the price of a share reflects the collective probability assigned by the market. Traders can place limit or market orders to enter or exit positions, and the spread between bid and ask prices tightens as liquidity grows. The platform's matching engine executes trades instantly, ensuring transparent price discovery throughout the trading window.

This market resolves around Jun 30, 2026, once June 29, 2026 has passed and the lowest temperature for that day in San Francisco is verified against credible public sources. The outcome is determined by the actual recorded minimum temperature from official weather monitoring stations serving the San Francisco area. Traders holding shares in the correct outcome band receive their payout, while incorrect positions expire worthless. Resolution typically occurs within hours of the close of the trading day.

Major weather pattern shifts, seasonal climate anomalies, and updated long-range forecasts from meteorological agencies can all move odds significantly. El Niño or La Niña conditions, unusual jet stream positioning, or heat waves or cold snaps affecting the broader West Coast may influence trader expectations. As June 2026 approaches, medium-range forecasts become more reliable, typically causing sharper repricing. Breaking news about atmospheric conditions, ocean temperatures, or climate indices in the weeks leading up to the event will likely trigger volume spikes and odds adjustments as traders incorporate fresh information.