Lowest temperature in Denver on Jun 13, 2026?

Prediction market odds often diverge from traditional meteorologist forecasts because they incorporate real-time trader behavior, financial incentives, and crowd wisdom. While weather analysts rely on numerical models and historical data, this market aggregates the beliefs of many participants betting their own capital on the outcome. Comparing the implied probability here to published seasonal forecasts or long-range weather outlooks can reveal where the crowd sees opportunity or risk that official models may not yet reflect, though both sources remain inherently uncertain for events months away.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares representing different temperature ranges or 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 the collective willingness of buyers and sellers to transact at that level, with tighter spreads indicating higher confidence and liquidity. As new information arrives—seasonal weather patterns, climate data, or forecaster updates—traders adjust their bids and offers, causing prices to move in real time and revealing shifting market expectations.

This market resolves around Jun 14, 2026, after June 13, 2026 has passed and the lowest temperature recorded in Denver that day becomes verifiable. The outcome is determined by comparing trader predictions against the actual low temperature reported from credible public sources, ensuring a transparent and objective settlement. Once the event data is confirmed, positions are settled and winnings distributed to those who correctly predicted the temperature range or threshold.

Several factors could shift odds significantly before resolution. Major climate pattern announcements, such as shifts in the jet stream or development of atmospheric systems expected to influence Colorado in June 2026, would likely trigger repricing. Long-range seasonal forecasts from NOAA or other meteorological agencies could alter trader expectations. Additionally, any significant updates to climate models, historical temperature anomalies, or broader weather trends affecting the region may prompt traders to adjust positions. Real-time market activity and changing trader sentiment will continuously reflect these evolving signals.