Lowest temperature in San Francisco on Jul 10, 2026?

Prediction market odds reflect real-time aggregation of trader beliefs and often diverge from traditional weather analyst forecasts. While meteorologists rely on physics-based models and historical climate data, this market incorporates diverse participant perspectives and incentivizes accuracy through financial stakes. Traders may price in factors analysts emphasize differently, such as atmospheric patterns, seasonal anomalies, or recent climate trends. Over time, prediction markets have demonstrated competitive accuracy against expert forecasts for weather events, though both approaches offer complementary insights into future conditions.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell shares corresponding to temperature ranges or specific outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices reflect the probability traders assign to each outcome, with higher prices indicating greater confidence in that scenario. As new weather data, forecasts, or seasonal information becomes available, traders adjust their positions, causing prices to move. The spread between bid and ask prices represents the current market uncertainty, tightening as the event date approaches and information becomes more concrete.

This market resolves around Jul 11, 2026, once July 10, 2026 has passed and the lowest temperature recorded in San Francisco that day is verified. The outcome is confirmed through credible public reporting from established weather data sources. Traders' positions settle based on whether the actual low temperature matches their predicted range or outcome. Resolution occurs shortly after the event concludes and official data is available, allowing all positions to be finalized and winnings distributed.

Several factors could shift odds significantly before resolution. Major climate pattern changes, such as unexpected heat waves or cold fronts affecting California, would trigger repricing. Updated seasonal forecasts from meteorological agencies, El Niño or La Niña developments, and historical temperature anomalies could influence trader positioning. Broader climate trends and recent Bay Area weather performance may also prompt adjustments. As July 2026 approaches, increasingly precise weather forecasts will narrow uncertainty and tighten the market range. Real-time atmospheric data and any unusual weather events in the months leading up to the date will drive continuous price discovery.