Lowest temperature in New Orleans on Jun 17, 2026?

Prediction market odds reflect aggregated trader expectations and often diverge from traditional meteorological forecasts because they incorporate real-time information, historical volatility, and market incentives. While weather analysts rely on deterministic climate models and historical data, this market prices in broader uncertainty and the collective judgment of participants betting real capital. Over time, prediction markets have shown competitive accuracy against expert forecasts for weather events, particularly when traders have access to updated model runs and satellite data. Comparing the implied probabilities here to National Weather Service or private meteorology firms can reveal where market participants see asymmetric risk.

On Kalshi, this market is priced through a continuous order-book mechanism 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 bracket has its own price, typically ranging from near-zero to near-100 cents per share, reflecting the probability traders assign to that range occurring. As new information arrives—updated seasonal models, climate patterns, or historical analogs—traders adjust their positions, moving prices up or down. The spread between bid and ask prices narrows during high-volume periods and widens when liquidity is thin, directly affecting transaction costs for participants entering or exiting positions.

This market resolves around Jun 18, 2026, after June 17, 2026 has passed and the lowest temperature for that day in New Orleans can be verified. The outcome is confirmed once credible public sources—such as the National Weather Service or established meteorological databases—report the official low temperature. Traders holding shares in the correct outcome bracket receive their payout, while incorrect positions expire worthless. Resolution typically occurs within 24–48 hours of the event date, once data has been finalized and cross-checked.

Major weather pattern shifts, updated seasonal forecasts, and historical climate anomalies can significantly move this market. El Niño or La Niña conditions, Arctic oscillation changes, and tropical system activity all influence June temperatures in the Gulf South. Real-time model consensus updates from the National Centers for Environmental Prediction and European weather services often trigger sharp repricing. Additionally, any unusual heat waves or cold snaps in the months preceding June 2026 may shift trader expectations about seasonal norms. As the event date approaches, daily forecast refinements and atmospheric pressure systems will drive incremental price adjustments.