Lowest temperature in San Francisco on Jun 17, 2026?

Prediction market odds reflect real-money bets from traders trying to forecast the lowest temperature on that specific date, whereas traditional analyst forecasts often rely on seasonal models and historical climate data. Markets tend to incorporate new information—such as updated weather patterns or atmospheric conditions—faster than static forecasts, since traders have a financial incentive to stay current. However, analyst models can offer detailed reasoning and uncertainty ranges that may not be obvious from market prices alone. Comparing this market's odds to published meteorological forecasts for mid-June 2026 can help you identify where expert opinion and trader consensus diverge.

On Kalshi, this market is priced through a continuous order book where traders buy and sell shares representing different temperature ranges or outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The bid-ask spread reflects the gap between what buyers and sellers are willing to agree on at any moment. As new trades execute, the price updates in real time, and the current odds tell you the implied probability the market is assigning to each outcome. Higher prices mean traders believe that outcome is more likely; lower prices suggest less conviction. You can place limit or market orders to enter or exit your position.

This market resolves around Jun 18, 2026, once the lowest temperature recorded in San Francisco on June 17, 2026 is verifiable from credible public sources. The outcome is determined by the actual meteorological data for that date, confirmed through official weather reporting. Once the event has occurred and the temperature is officially recorded, the market will settle based on which outcome bracket or range the verified low falls into. All open positions will be paid out according to the final result.

Several factors could shift trader expectations and move prices in this market. Major climate pattern changes—such as the development of an unusual high-pressure system or unexpected cold front—would likely trigger repricing. Updated seasonal forecasts from meteorological agencies, shifts in El Niño or La Niña conditions, and historical temperature anomalies for early June could all influence how traders assess the probability of warmer or cooler outcomes. As June 2026 approaches, short-term weather models will become more reliable and may cause sharp price moves. Real-time weather alerts and atmospheric data releases in the days leading up to June 17 will be key catalysts for final market adjustments.