Lowest temperature in New Orleans on Jun 23, 2026?

Prediction market odds reflect real-money trader conviction and aggregate dispersed information, often diverging from traditional meteorological forecasts. While weather analysts rely on numerical models and historical climatology, this market incorporates trader beliefs about model accuracy, potential anomalies, and long-range uncertainty. The two approaches can differ significantly months ahead of the event; markets may price in tail risks or consensus shifts that analysts haven't yet emphasized, making side-by-side comparison useful for understanding where professional and crowd expectations diverge.

On Kalshi, this market is priced through a continuous 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 in real time as new bids and asks arrive, with the spread between buy and sell prices reflecting liquidity and disagreement. Each outcome's price directly translates to an implied probability, so a higher price signals stronger market confidence in that temperature band occurring on the target date.

This market resolves around Jun 24, 2026, after June 23, 2026 has passed and the lowest temperature for that day is verifiable from credible public sources. The outcome is determined by the actual recorded minimum temperature in New Orleans on that date, confirmed through official meteorological data. Once the event occurs and the reading is finalized, the market settles according to whichever outcome bracket or threshold the verified temperature falls into.

Major climate patterns, seasonal forecasts, and long-range weather models will influence trader positioning over the coming months. El Niño or La Niña conditions, shifts in the jet stream, and historical anomalies for late June in New Orleans all carry weight. As June 2026 approaches, updated medium-range forecasts will drive sharper repricing. Additionally, any unusual heat waves or cold snaps in the months prior may shift expectations about atmospheric conditions, causing traders to adjust their bets on the final temperature outcome.