Lowest temperature in Boston on Jun 17, 2026?

Prediction market odds reflect real-money trading by participants with skin in the game, often incorporating private research and proprietary models alongside public forecasts. While meteorologists and climate analysts publish seasonal outlooks and historical temperature patterns, this market aggregates those signals plus trader conviction into a single probability. The two approaches differ in methodology: analysts rely on physics-based models, while markets price in broader uncertainty and tail risks. Over time, markets tend to incorporate analyst consensus but may diverge when traders identify overlooked factors or when confidence in forecasts is low.

On Kalshi, this market is priced through a continuous order-book mechanism where traders submit bids and asks for shares corresponding to different temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each outcome reflects supply and demand; as more traders buy shares predicting a colder day, that outcome's price rises, and vice versa. Settlement values are tied to verified temperature data, ensuring that final payouts reflect the actual lowest temperature recorded on the specified date. This transparent pricing model lets you enter or exit positions at any time before resolution.

This market resolves around Jun 18, 2026, once the lowest temperature for June 17, 2026 in Boston is confirmed and verifiable from credible public sources. The outcome is determined by the actual minimum temperature recorded on that date, measured at an official weather station or recognized meteorological authority. Traders holding shares in the outcome bracket that matches the final temperature receive their payout, while other positions expire worthless. The resolution process is automated once the data is published and validated.

Major climate patterns, seasonal forecasts, and long-range weather models will drive significant price swings as June 2026 approaches. El Niño or La Niña conditions, Arctic oscillation shifts, and Atlantic hurricane activity can all influence summer temperatures in Boston. Closer to the event date, medium-range forecasts from the National Weather Service and European models become more reliable and often trigger sharp repricing. Additionally, historical anomalies—such as unexpected cold snaps or heat waves in prior years—may prompt traders to adjust their positions as new data emerges.