Lowest temperature in San Francisco on Jun 23, 2026?

Prediction market odds often diverge from traditional meteorological forecasts because they incorporate real-time trader behavior, uncertainty premiums, and collective intelligence beyond a single model. While weather analysts rely on physics-based atmospheric models and historical data, this market aggregates the beliefs of many participants with financial incentives to forecast accurately. Traders may price in tail risks or seasonal patterns that formal forecasts downweight. Over time, prediction markets have proven competitive with or superior to expert predictions in many domains, though both approaches offer complementary perspectives on what the lowest temperature will be on that date.

On Kalshi, this market is priced through a continuous order-book mechanism where buyers and sellers submit bids and offers across discrete temperature outcome ranges. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each outcome reflects the ratio of capital backing that outcome to total capital in the market, expressed as an implied probability. As traders buy or sell contracts, the price adjusts in real time. Lower temperatures and higher temperatures are typically offered as separate contracts, and the spread between bid and ask prices narrows or widens based on liquidity and conviction among participants.

This market resolves around Jun 24, 2026, once the lowest temperature recorded in San Francisco on June 23, 2026 is verifiable from credible public sources. The outcome is determined by the actual meteorological data reported for that date, typically from the National Weather Service or equivalent official weather station records. Traders' positions settle based on which temperature range the verified low falls into. The resolution process is automated once the data becomes available, ensuring all participants receive payouts according to their contract holdings and the final outcome.

Major weather pattern shifts, seasonal climate anomalies, and updated long-range forecasts from meteorological agencies can significantly move this market. El Niño or La Niña conditions, unusual jet stream positioning, or historical temperature records for early summer in San Francisco may influence trader expectations. As June 2026 approaches, short-range forecasts become more reliable and can trigger sharp repricing. Additionally, broader climate trends, atmospheric pressure systems developing weeks in advance, and any unusual solar or oceanic activity could shift the collective forecast. Real-time weather updates in the days leading up to June 23 will likely create the most volatile price movements.