Highest temperature in NYC on Jun 22, 2026?

Prediction market odds reflect aggregated trader expectations and often diverge from traditional weather forecasts issued by meteorologists or climate analysts. While institutional forecasters rely on atmospheric models and historical data, this market incorporates real-time information, trader conviction, and forward-looking sentiment. Comparing the implied probability from current odds to published forecasts from the National Weather Service or similar bodies can reveal whether traders are pricing in more or less extreme heat than official models suggest for that date.

On Kalshi, this market is priced through continuous order-book matching, where traders buy and sell shares corresponding to specific temperature ranges. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome band has its own bid-ask spread, and the midpoint price converts directly to an implied probability. As new information emerges—seasonal forecasts, climate patterns, or real-time weather data—traders adjust positions, moving prices and shifting the probability distribution across all temperature brackets.

This market resolves around Jun 23, 2026, once June 22, 2026 has passed and the actual high temperature for New York City is confirmed. The outcome is determined by the verified daily maximum temperature recorded on that date, with the result anchored to credible public weather reporting. Traders holding shares in the outcome band matching the final recorded high receive their payout, while all other positions expire worthless.

Several factors can shift odds in this market: updated seasonal climate forecasts, El Niño or La Niña patterns affecting North American weather, anomalous heat waves or cold snaps in preceding weeks, and real-time atmospheric data as June 2026 approaches. Major weather events in late spring can reset trader expectations for early summer temperatures. Additionally, any shifts in long-range climate models or unexpected atmospheric circulation changes will likely trigger repricing across outcome bands as traders adjust their conviction on whether the day will be unusually hot, moderate, or cool.