Lowest temperature in San Francisco on Jun 25, 2026?

Prediction market odds often diverge from traditional meteorological forecasts because they incorporate real-time trader sentiment and broader uncertainty. While weather analysts issue deterministic point estimates or narrow ranges based on atmospheric models, this market prices multiple temperature bands simultaneously, reflecting the full distribution of possible outcomes. Traders may weight tail risks—extreme cold snaps or unusual warming—differently than statistical models do. Over time, prediction markets have demonstrated competitive accuracy against expert forecasts, particularly when aggregating diverse participant views. Comparing the two approaches reveals how markets price information that conventional forecasts may underweight or overlook.

On Kalshi, this market is priced through an order-book mechanism where traders submit bids and offers for each temperature outcome band. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices reflect the probability implied by supply and demand; a higher price indicates traders believe that outcome is more likely. Each outcome is a separate contract, and the sum of all outcome prices should approximate 100 cents if the market is well-calibrated. Traders profit by correctly predicting which temperature range will occur, with payouts determined by their entry price and the final verified outcome. Liquidity and spreads vary depending on trading activity and proximity to the resolution date.

This market resolves around Jun 26, 2026, once the lowest temperature for June 25, 2026 in San Francisco is verifiable from credible public sources. The outcome is determined by the actual minimum temperature recorded on that date, confirmed through established meteorological data. Traders holding shares in the correct outcome band receive their payout based on the contract price at which they entered. Resolution typically occurs within hours of the market close, pending final data verification. The specific temperature thresholds defining each outcome band are detailed in the market's terms.

Several factors could shift odds significantly before resolution. Major weather pattern changes—such as an unexpected cold front, heat dome, or atmospheric disturbance—would trigger rapid repricing as traders update their forecasts. Seasonal climate anomalies, El Niño or La Niña developments, and long-range model updates from meteorological agencies often spark trading surges. As June 2026 approaches, short-range forecasts become more reliable, typically narrowing the range of plausible outcomes and concentrating liquidity around the most probable bands. Breaking news about unusual atmospheric conditions or historical temperature records could also influence trader positioning. Proximity to resolution date generally increases volatility as uncertainty resolves.