Lowest temperature in Houston on Jun 22, 2026?

Prediction market odds often diverge from traditional meteorologist forecasts because they incorporate real-time trader conviction and incentivize accuracy through financial stakes. While weather analysts rely on numerical models and historical data, this market aggregates dispersed information from many participants betting their own capital. Comparing odds here to published forecasts from the National Weather Service or private meteorology firms can reveal where the crowd expects surprises or systematic model bias. Over time, markets tend to outperform single-source predictions, though both approaches have merit for understanding likely temperature ranges.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell shares corresponding to different temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome has its own price, reflecting the collective probability the crowd assigns to that range. As new information arrives—seasonal forecasts, climate patterns, or real-time weather updates—traders adjust their positions, moving prices up or down. The spread between bid and ask prices narrows or widens based on liquidity and disagreement among participants, directly influencing your entry and exit costs.

This market resolves around Jun 23, 2026, once the lowest temperature recorded in Houston on June 22, 2026 is verified against credible public sources. The outcome is determined by official meteorological data, typically from the National Weather Service or equivalent authoritative weather station records for the Houston area. Resolution occurs shortly after the calendar day closes and the final temperature reading is confirmed. Traders holding positions in the winning outcome receive their payout based on the market's final price.

Major weather pattern shifts, seasonal climate forecasts, and long-range atmospheric models will drive price movement in this market. El Niño or La Niña conditions, polar vortex behavior, and upper-atmosphere jet stream positioning can all influence June temperatures in Houston. Real-time updates from meteorological agencies and anomalous heat or cold events in late spring may trigger rapid repricing. Additionally, historical June temperature records and emerging climate trends will inform trader expectations. As the event date approaches, short-range forecasts will become increasingly precise, potentially causing sharp volatility in the final weeks.