Lowest temperature in San Francisco on Jul 3, 2026?

Prediction market odds often diverge from traditional weather forecasts because they reflect real-money stakes and continuous price discovery rather than a single model snapshot. While meteorologists publish deterministic or probabilistic forecasts based on atmospheric data, this market aggregates the collective judgment of traders betting on the actual outcome. Prediction markets tend to update faster as new information emerges and can capture tail risks that models underweight. However, both approaches have merit: analyst forecasts bring domain expertise and physics-based modeling, while market odds incorporate diverse perspectives and financial incentives for accuracy. Comparing the two can reveal where consensus is strong or where uncertainty remains high heading into July 3, 2026.

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 outcome contract trades independently, and the price of each reflects the collective willingness to bet on that specific temperature range. Traders can place limit or market orders, and the spread between bid and ask prices represents the current uncertainty around the lowest temperature. As new information arrives or market sentiment shifts, prices adjust in real time. The platform's matching engine ensures transparent price discovery, allowing participants to enter or exit positions at any time before the market closes on Jul 4, 2026.

This market resolves around Jul 4, 2026, after the close of trading and once the lowest temperature for July 3, 2026 in San Francisco is verifiable from credible public sources. The outcome is determined by the actual recorded low temperature on that date, confirmed through official weather data. Traders holding shares in the correct outcome band receive their payout, while incorrect positions expire worthless. The resolution process is automated once the temperature data is finalized and published, ensuring all participants see the same definitive result. No manual intervention or discretionary judgment is involved in determining which outcome occurred.

Several factors can shift odds in this market as July 3, 2026 approaches. Major weather pattern changes, such as shifts in high-pressure systems or unexpected marine layer behavior, will influence trader expectations. Seasonal climate anomalies or longer-term trends in San Francisco's summer temperatures may also prompt repricing. As the date draws closer, updated meteorological forecasts and ensemble model runs become more precise, often triggering significant price moves. Real-time atmospheric data, including upper-level wind patterns and moisture levels, can surprise the market if conditions deviate from earlier expectations. Additionally, any unusual heat events or cold snaps in the weeks leading up to July 3 may shift baseline assumptions about what constitutes a likely low temperature for that specific day.