Highest temperature in Minneapolis on Jun 30, 2026?

Prediction market odds reflect real-money bets from traders who have studied weather models, historical data, and seasonal trends. Unlike traditional forecasts from meteorologists or climate analysts, this market aggregates dispersed knowledge through price discovery—traders profit only if their temperature prediction proves accurate. Analyst forecasts tend to be point estimates or ranges; prediction markets instead express confidence as odds. Over time, markets often incorporate new information faster than static forecasts, making them a useful cross-check against conventional weather outlooks for this specific date and location.

On Kalshi, this market is priced through a continuous order book 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 has a bid-ask spread; you pay the ask price to go long (bet on a higher temperature) or receive the bid price to go short (bet on a lower temperature). The market price reflects the marginal trader's belief about the likelihood of each outcome. As new information emerges—updated weather models, seasonal anomalies, or climate data—traders adjust their positions, and prices move to reflect the new consensus.

This market resolves around Jul 1, 2026, once June 30, 2026 has passed and the highest temperature recorded in Minneapolis that day is verified against credible public sources. The outcome is determined by the official high temperature for that date, measured in degrees Fahrenheit. Traders holding shares in the correct outcome receive their payout; all other positions expire worthless. The resolution process is automatic once the data is confirmed, ensuring a fair and transparent settlement for all participants.

Major shifts in long-range weather forecasts, updated climate models, and seasonal anomaly reports can drive significant price moves in this market. El Niño or La Niña patterns, jet stream positioning, and historical temperature records for late June in Minneapolis all influence trader expectations. As the date approaches, short-range forecasts from the National Weather Service become more reliable and typically trigger sharper repricing. Unusual heat waves or cold snaps in the broader Midwest region may also signal changing atmospheric conditions. Real-time monitoring of meteorological data and seasonal outlooks will help you stay ahead of market repricing.