Lowest temperature in Houston on Jun 29, 2026?

Prediction market odds reflect aggregated trader expectations and often diverge from traditional meteorological forecasts. While weather analysts rely on atmospheric models and historical climate data for June conditions in Houston, this market prices in real-time information and trader conviction. Markets can sometimes lead or lag official forecasts depending on data availability and participant confidence. Comparing the implied probability here to published seasonal outlooks from meteorological services provides useful context for assessing market efficiency and identifying potential mispricings.

On Kalshi, this market is priced through a continuous order-book mechanism 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 represents a distinct temperature band, and the current bid-ask spread reflects the market's uncertainty around the lowest temperature on that date. Traders profit by correctly predicting which range will verify, incentivizing accurate pricing as new weather data becomes available closer to the event.

This market resolves around Jun 30, 2026, once the lowest temperature recorded in Houston on June 29, 2026 is verified against credible public sources. The outcome is determined by comparing the actual minimum temperature to the predefined ranges offered in the market. Traders holding shares in the correct outcome receive their payout once the event is confirmed and the market settles.

Major weather pattern shifts, seasonal climate anomalies, and updated long-range forecasts can significantly move odds in this market. El Niño or La Niña conditions, atmospheric pressure systems, and historical temperature records for late June in Houston all serve as important signals. As June 2026 approaches, real-time meteorological updates and short-range forecasts will increasingly influence trader positioning. Unexpected climate events or revisions to seasonal outlooks may also trigger sharp repricing before the market closes.