Lowest temperature in Boston on Jul 2, 2026?

Prediction market odds often diverge from traditional weather forecasts because they aggregate real-time trader expectations rather than relying on a single meteorological model. While meteorologists publish deterministic low-temperature predictions based on atmospheric data, this market allows traders to price in uncertainty, tail risks, and late-breaking weather pattern shifts. Comparing the implied probabilities here to published forecasts from the National Weather Service or private weather services can reveal where the crowd expects surprises or where consensus is strongest.

On Kalshi, this market is priced through an order-book mechanism 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 contract trades independently, and the price of a share reflects the crowd's estimated probability of that outcome occurring. As new information emerges—updated forecasts, seasonal patterns, or atmospheric developments—traders adjust their bids and asks, causing prices to move and the implied odds to shift dynamically.

This market resolves around Jul 3, 2026, after July 2, 2026 concludes. The outcome is determined by the verified lowest temperature recorded in Boston on that date, confirmed once the event is verifiable from credible public reporting. Traders holding shares in the correct temperature range at resolution receive their payout, while incorrect positions expire worthless. The exact temperature threshold boundaries are set at market creation and remain fixed throughout the trading period.

Major weather pattern shifts, seasonal anomalies, and updated long-range forecasts from meteorological agencies can significantly move this market. Unexpected climate events, changes in atmospheric circulation, or revised seasonal outlooks may prompt traders to reassess probabilities. Additionally, as the event date approaches, short-range forecasts become more precise and reliable, typically causing prices to converge toward the most likely outcome. Real-time weather developments and model consensus shifts in the days leading up to July 2 will likely drive the most volatile trading activity.