Lowest temperature in New Orleans on Jun 29, 2026?

Prediction market odds often diverge from traditional weather forecasts because they incorporate real-time trader behavior, risk premiums, and longer-term uncertainty. While meteorologists typically issue high-confidence forecasts only days in advance, this market aggregates beliefs from many participants trading months ahead. Analyst models may emphasize historical climate patterns and seasonal norms, whereas traders price in tail risks and unusual scenarios. Comparing the implied probability in this market to published forecasts from the National Weather Service or other meteorological agencies can reveal whether traders are pricing in more or less downside risk than official predictions suggest.

On Kalshi, this market is priced through a continuous order-book mechanism where buyers and sellers submit bids and offers for each temperature outcome. 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 marginal cost of acquiring or selling a contract, and the sum of all outcome prices equals one dollar. As traders update their views on the likelihood of different temperature ranges, they adjust their orders, causing prices to move in real time. Tighter spreads between bid and ask prices typically indicate higher confidence and liquidity around certain outcomes.

This market resolves around Jun 30, 2026, once the lowest temperature recorded in New Orleans on June 29, 2026 is verified and confirmed. The outcome is determined by the actual low temperature observed on that date, measured against the predefined outcome ranges offered in the market. Resolution occurs after the event concludes and the data is confirmed from credible public sources. Traders holding contracts corresponding to the verified outcome receive their payout, while other positions expire worthless.

Several factors may shift odds in this market over the coming months. Major weather pattern changes—such as shifts in the jet stream, tropical storm activity, or anomalous high or low pressure systems—can alter long-range forecasts and trader sentiment. El Niño or La Niña transitions, seasonal climate oscillations, and historical temperature records for late June in New Orleans all provide context traders monitor. As the event date approaches, official extended forecasts become more precise, typically triggering repricing. Unusual heat waves or cold snaps elsewhere in the region may also influence expectations for New Orleans conditions.