Lowest temperature in San Francisco on Jul 6, 2026?

Prediction market odds reflect real-money trader conviction and often diverge from traditional meteorological forecasts because they incorporate broader information—including historical patterns, climate data, and near-term weather models. While meteorologists issue point estimates or ranges based on atmospheric science, this market prices uncertainty through continuous trading. Comparing the two reveals whether traders are more bullish or bearish on cooler conditions than official forecasts suggest, making prediction markets a useful cross-check for understanding consensus expectations around the lowest temperature on that date.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell binary or range-based outcome shares. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome contract reflects the probability traders assign to that temperature bracket, with prices ranging from near zero to near one dollar. As new information emerges—updated forecasts, seasonal trends, or atmospheric patterns—traders adjust their positions, moving prices in real time. The spread between bid and ask prices indicates market liquidity and confidence in the outcome.

This market resolves around Jul 7, 2026, after July 6, 2026 has passed and the lowest temperature can be verified from credible public sources. The outcome is determined by the actual recorded low temperature in San Francisco on that date, confirmed through official weather reporting. Once the data is finalized and cross-checked against reliable meteorological records, the market settles and winning positions are paid out according to which temperature bracket the verified low falls into.

Several factors could shift odds significantly before resolution. Updated seasonal forecasts, El Niño or La Niña patterns, and long-range climate models may alter trader expectations. Unusual heat waves or cold snaps in preceding weeks could signal shifts in July weather. Real-time meteorological updates closer to the date—particularly 10-day forecasts—typically drive sharp repricing. Additionally, historical temperature records for early July and any anomalies in spring or early summer conditions may prompt traders to reassess their positions, creating volatility in this market as new information accumulates.