Highest temperature in Boston on Jun 17, 2026?

Prediction market odds reflect real-time consensus from traders betting on specific temperature outcomes, while meteorological forecasts from the National Weather Service and private weather services rely on physics-based models and historical climate data. This market aggregates dispersed trader knowledge into a single price signal, which often diverges from traditional forecasts because markets incorporate broader information sources and incentivize accuracy through financial stakes. Both approaches offer value: markets capture collective judgment, while analyst models provide detailed physical reasoning.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to different temperature ranges or specific outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices move continuously as new orders flow in, reflecting shifts in trader confidence about the June 17 high. The spread between bid and ask prices indicates liquidity; tighter spreads suggest strong consensus, while wider spreads reflect uncertainty or lower trading volume.

This market resolves around Jun 18, 2026, once the actual highest temperature recorded in Boston on June 17, 2026 becomes verifiable from credible public sources. The outcome is determined by official weather station data, typically from the National Weather Service or equivalent meteorological authority. Resolution occurs shortly after the day concludes and the final temperature is confirmed.

Major shifts in seasonal climate patterns, El Niño or La Niña conditions, and updated long-range forecasts from meteorological agencies can all influence trader expectations and move prices significantly. As June 2026 approaches, near-term weather models become more reliable, typically narrowing the range of likely outcomes. Unusual heat waves, atmospheric blocking patterns, or shifts in jet stream behavior reported in the media may also trigger sharp repricing as traders reassess probabilities.