Lowest temperature in San Francisco on Jul 7, 2026?

Prediction market odds often diverge from traditional weather forecasts because they incorporate real-time trader sentiment and financial incentives alongside meteorological models. While meteorologists rely on atmospheric data and historical patterns, this market aggregates the views of participants who have money at stake, sometimes surfacing early signals or alternative scenarios that formal forecasts may underweight. Comparing the implied probabilities here to published analyst predictions for San Francisco's July 7 low can reveal where the market sees additional risk or opportunity. Neither source is inherently superior; together they provide complementary perspectives on the likely outcome.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to different temperature ranges. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome has its own contract, and the price of each reflects the probability traders assign to that range occurring. As demand shifts—driven by new weather data, seasonal patterns, or model updates—the bid-ask spread widens or tightens, and prices move accordingly. You can place limit or market orders to enter or exit positions, and your profit or loss is determined by the difference between your entry and exit prices.

This market resolves around Jul 8, 2026, after July 7, 2026 has passed and the lowest temperature for that day in San Francisco can be verified. The outcome is determined by comparing the actual recorded low against the temperature thresholds defined in each contract. Once credible public reporting confirms the final low, the market settles and winning positions are credited automatically. Traders should monitor official weather data sources in the days leading up to and immediately following the event to anticipate the likely resolution.

Major weather pattern shifts, seasonal anomalies, and updated climate forecasts can all drive significant price movement in this market. El Niño or La Niña conditions, unexpected jet stream behavior, or heat waves affecting the West Coast may prompt traders to revise their temperature expectations upward or downward. Additionally, historical precedent—such as record lows or highs for early July in San Francisco—often influences positioning. As the event date approaches, short-term forecasts become more reliable, typically causing the market to narrow its range and converge toward the most likely outcome. Real-time weather alerts and model consensus shifts will be key catalysts.