Lowest temperature in San Francisco on Jul 11, 2026?

Prediction market odds reflect real-money trades from participants who research weather patterns, historical data, and seasonal trends for the San Francisco Bay Area. Unlike traditional analyst forecasts, which rely on individual meteorologist models, this market aggregates the collective judgment of many traders with direct financial incentive to be accurate. Comparing the implied probabilities here to published forecasts from the National Weather Service or private meteorological firms can reveal where the crowd expects conditions to diverge from official predictions. Markets often incorporate emerging data faster than periodic analyst updates.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell shares corresponding to each temperature outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each share pays out a fixed amount if that outcome occurs, and the current market price of a share reflects the crowd's estimated probability. Traders can enter limit or market orders, and the spread between bid and ask prices tightens as volume increases. The price discovery process ensures that all available information about San Francisco's expected low temperature on that date is reflected in real time.

This market resolves around Jul 12, 2026, after July 11, 2026 has passed and the actual lowest temperature in San Francisco can be verified. The outcome is confirmed once credible public sources report the official low temperature for that day. Traders holding shares in the correct outcome bracket receive their payout automatically. Until that point, prices will fluctuate based on updated weather forecasts, seasonal patterns, and real-time trading activity.

Major weather pattern shifts, such as unexpected atmospheric changes or anomalous jet stream behavior, could significantly move prices in this market. Seasonal climate reports, El Niño or La Niña developments, and updated long-range forecasts from meteorological agencies will influence trader positioning. As July 2026 approaches, short-range weather models become more reliable and typically drive sharper price moves. Historical temperature records for San Francisco in early July and any unusual heat or cold events in the months leading up to the date may also prompt traders to reassess their positions.