Lowest temperature in New Orleans on Jun 21, 2026?

Prediction market odds reflect aggregated trader expectations and often diverge from traditional meteorological forecasts. While weather analysts rely on deterministic climate models and historical data, this market prices in real-time information, trader conviction, and tail-risk scenarios. Comparing the implied probability from market odds to published seasonal outlooks or long-range forecasts from the National Weather Service can reveal where traders see asymmetric opportunities. Markets tend to update faster than formal forecasts when new data arrives, making them a complementary signal rather than a replacement for expert analysis.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to temperature ranges or specific outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices move based on supply and demand; as more traders believe the low will fall within a certain band, the cost of those shares rises. Each contract represents a claim on a discrete outcome, and the sum of all outcome prices reflects the market's aggregate forecast. Liquidity and spreads vary throughout the trading day, so timing your entry or exit can affect the price you receive.

This market resolves around Jun 22, 2026, once the event has occurred and the lowest temperature for June 21, 2026 in New Orleans can be verified from credible public sources. The outcome is determined by comparing actual recorded temperatures against the predefined thresholds or ranges embedded in the contract. Traders holding shares in the correct outcome receive their payout, while incorrect positions expire worthless. The resolution process is final once the data is confirmed and published.

Several factors could shift odds significantly before June 2026. Updated seasonal climate forecasts, particularly those indicating stronger or weaker La Niña or El Niño patterns, often trigger repricing. Major weather events in the preceding months may alter trader expectations about atmospheric conditions. Long-range model consensus shifts, changes in solar activity predictions, or emerging climate anomalies can all influence how traders assess the probability of extreme cold or warmth. As June approaches, near-term weather patterns and real-time atmospheric data will dominate price movements, potentially creating sharp reversals if conditions deviate from earlier expectations.