Lowest temperature in New York City on Jun 24, 2026?

Prediction market odds often diverge from traditional weather analyst forecasts because traders incorporate real-time data, model uncertainty, and their own risk assessments into prices. While meteorologists issue point forecasts or confidence intervals based on numerical weather models, this market aggregates the distributed knowledge of many participants betting their own capital. Comparing the implied temperature range from market odds to the National Weather Service or other official forecasts can reveal where traders see higher or lower probability than experts, offering an alternative perspective on the likely outcome for that day.

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 reflects the probability traders assign to that temperature band, with prices ranging from near zero to near 100 cents per share. As new information arrives—updated forecasts, seasonal patterns, or real-time weather developments—traders adjust their bids and offers, moving prices to reflect the latest consensus. The spread between buy and sell prices indicates market confidence and liquidity for each outcome.

This market resolves around Jun 25, 2026, after the close of trading and once the day's low temperature is verifiable from credible public sources. The outcome is determined by the official recorded low temperature in New York City on June 24, 2026, confirmed through established meteorological reporting. Once the data is finalized and cross-checked, the market settles to the outcome that matches the verified temperature, and traders' positions are paid out accordingly based on which outcome they held.

Major weather model updates, seasonal climate patterns, and atmospheric pressure systems will drive significant price movement in this market. Tropical systems, heat domes, or cold fronts approaching the Northeast in late June could shift trader expectations sharply. Real-time satellite imagery, upper-atmosphere data, and official National Weather Service advisories typically trigger repricing as the event date approaches. Additionally, historical temperature records for that date and broader climate anomalies may influence how traders assess the probability of extreme outcomes, causing volatility in the final days before resolution.