Lowest temperature in San Francisco on Jul 4, 2026?

Prediction market odds often diverge from traditional meteorological forecasts because they incorporate real-time trader conviction and broader information flows. While weather analysts rely on numerical models and historical patterns, this market aggregates the collective judgment of participants who have financial incentive to forecast accurately. Comparing the implied probability from market odds to published forecasts from the National Weather Service or other agencies can reveal where traders see asymmetric risk. Markets tend to update faster than static seasonal outlooks, making them a complementary signal for understanding expected temperature ranges.

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 carries 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, the market price adjusts in real time. Your position's value depends on whether the final verified temperature aligns with your chosen outcome, making the pricing mechanism transparent and directly tied to actual event resolution.

This market resolves around Jul 5, 2026, once July 4, 2026 has passed and the lowest temperature for San Francisco can be verified. The outcome is determined by the actual recorded low temperature on that date, confirmed against credible public sources. Traders holding shares in the outcome range that contains the verified temperature receive their payout, while other positions expire worthless. The resolution process is automated once the data is available, ensuring all participants receive timely settlement.

Several factors can shift odds in this market before resolution. Updated seasonal climate forecasts, El Niño or La Niña patterns, and historical temperature anomalies for early July in San Francisco all influence trader positioning. Major weather pattern changes—such as shifts in the jet stream or unexpected high-pressure systems—can trigger repricing. Additionally, as July 4, 2026 approaches, real-time weather models become more precise, typically narrowing the range of plausible outcomes and concentrating liquidity around the most likely temperature bands. Traders monitoring long-range forecasts and atmospheric indices often adjust positions weeks in advance.