Highest temperature in San Antonio on Jun 14, 2026?

Prediction market odds aggregate the collective judgment of traders betting real money on outcomes, whereas traditional analyst forecasts rely on meteorological models and expert opinion. This market incorporates forward-looking trader behavior and incentives to be accurate, often capturing shifts in expectations faster than static forecasts. Comparing odds here to published weather forecasts from the National Weather Service or other meteorological authorities can reveal where the market expects conditions to diverge from baseline predictions. Both sources offer value: markets excel at pricing uncertainty, while institutional forecasters provide detailed physical reasoning.

On Kalshi, this market is priced through a continuous order book 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 an implied probability reflected in its current price, and traders profit by correctly predicting which temperature band will verify as accurate. The bid-ask spread tightens as volume increases and resolution approaches, making prices more efficient. Kalshi's regulatory framework ensures transparent pricing and settlement aligned with verifiable real-world data.

This market resolves around Jun 15, 2026, once the highest temperature recorded in San Antonio on June 14, 2026 is verified and confirmed. The outcome is determined by comparing the final temperature reading against the predefined ranges offered in the market. Resolution depends on credible public reporting of the actual high temperature for that date, ensuring all traders have access to the same authoritative information. Kalshi will settle all positions based on the verified result.

Major weather pattern shifts, seasonal climate anomalies, and updated long-range forecasts from meteorological agencies will influence trader positioning in this market. El Niño or La Niña conditions, atmospheric pressure systems, and historical temperature records for mid-June in San Antonio all serve as reference points. As June 14, 2026 approaches, short-range weather models become more precise, typically causing prices to converge toward a narrower range. Breaking news about climate events or unusual atmospheric conditions could trigger rapid repricing as traders adjust their expectations.