Lowest temperature in San Francisco on Jul 5, 2026?

Prediction market odds reflect real-money trader conviction and often diverge from traditional meteorological forecasts because markets incorporate broader information sets, including historical patterns, climate data, and trader expertise. While weather analysts publish deterministic point forecasts or confidence intervals, this market prices uncertainty through continuous trading. Comparing the implied probabilities here to National Weather Service or other official forecasts can reveal where the crowd sees asymmetric risk—for instance, if traders price a cold snap higher than meteorologists expect, that gap may signal underappreciated catalysts or model disagreement.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell binary or range-based contracts reflecting their belief about the lowest temperature outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Share prices move in real time as new orders flow in, with the bid-ask spread reflecting uncertainty and liquidity. Each contract represents a specific temperature threshold or range, and the market price directly translates to an implied probability that traders assign to that outcome occurring on the event date.

This market resolves around Jul 6, 2026, once July 5, 2026 has passed and the lowest temperature for that day in San Francisco can be verified. The outcome is confirmed against credible public sources documenting the actual low temperature recorded in the city. Traders holding contracts aligned with the verified outcome receive their payouts, while misaligned positions expire worthless. Resolution timing depends on data availability and platform processing, typically occurring within hours of the close of the trading day.

Major catalysts include updated seasonal climate forecasts, El Niño or La Niña patterns affecting Pacific weather, and any unusual atmospheric circulation anomalies predicted months in advance. Real-time signals closer to July 2026 will include weekly weather model runs, historical temperature comparisons for that date, and any documented climate shifts. Trader positioning itself can shift rapidly if new scientific data emerges or if similar markets on nearby dates show unexpected moves, creating arbitrage opportunities that ripple through this market's price.