Lowest temperature in San Francisco on Jun 8, 2026?

Prediction market odds on Kalshi reflect aggregated trader expectations and often diverge from traditional meteorological forecasts. While weather analysts rely on historical climate data and seasonal models, prediction markets incorporate real-time information, trader conviction, and financial incentives. Markets may price in tail risks or unusual patterns that analysts downweight. Comparing Kalshi odds to National Weather Service seasonal outlooks or climate reports can reveal whether traders expect warmer or cooler conditions than historical norms suggest. This comparison highlights how market-based probability differs from statistical forecasting.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the lowest temperature in San Francisco on June 8 is priced as a set of binary or range-based contracts, each representing a specific temperature threshold or band. Traders buy and sell shares reflecting their belief in whether the actual low will fall within that range. Prices fluctuate based on supply and demand, with higher prices indicating stronger market confidence in that outcome. As new weather data emerges or seasonal patterns become clearer, contract prices adjust. The market structure allows precise temperature forecasting while maintaining liquidity around the most likely outcomes.

The market resolves on Jun 9, 2026, after June 8 has concluded and the official lowest temperature for San Francisco is recorded. Resolution is determined by the actual observed low temperature on that date, sourced from an authoritative weather data provider. Once the final temperature is confirmed, the contract corresponding to the correct outcome is settled at full value, and all other outcomes expire worthless. This timing ensures sufficient data collection and verification before payouts are distributed to winning traders.

Several factors could shift odds for San Francisco's June 8 low temperature. Major weather pattern changes—such as shifts in the Pacific jet stream, formation of high or low-pressure systems, or unusual ocean temperature anomalies—often trigger significant repricing. Seasonal climate forecasts released by NOAA or other meteorological agencies can move markets if they signal warmer or cooler conditions ahead. Real-time weather model updates in the days leading up to June 8 typically cause the most dramatic price swings. Additionally, historical precedent for early June temperatures in San Francisco and any unusual atmospheric events may influence trader positioning.