Lowest temperature in Dallas on May 31, 2026?

Prediction market odds on Kalshi reflect real-money trader expectations for Dallas's lowest temperature on May 31, 2026, and can be compared against meteorological forecasts from the National Weather Service and private weather services. Markets typically incorporate longer-term climate patterns and seasonal trends, while traditional forecasts rely on atmospheric modeling closer to the event date. As May 31 approaches, convergence between market odds and official forecasts often increases, though market prices may lead or lag analyst updates depending on new data releases.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the lowest temperature in Dallas on May 31, 2026, is priced as a binary or range-based contract reflecting trader belief in specific temperature thresholds. Each outcome contract trades independently, with prices ranging from 0 to 100 cents, where the implied probability equals the price divided by 100. Traders buy contracts they believe will resolve true and sell those they expect to resolve false. Kalshi's order book displays real-time bids and asks, allowing you to enter limit or market orders based on your temperature forecast.

The market resolves on Jun 1, 2026, after the close of trading on May 31, 2026. Resolution is determined by the official lowest temperature recorded in Dallas on that date. The specific data source and measurement methodology are defined in the market's terms at contract inception. Once the official temperature is published, the outcome is settled automatically, and winning contracts are credited to trader accounts.

Market prices for Dallas's lowest temperature on May 31, 2026, will shift in response to seasonal weather pattern updates, long-range forecasts from meteorological agencies, and historical climate anomalies. El Niño or La Niña conditions, jet stream positioning, and high-altitude pressure systems can influence late-May temperatures in Texas. As May approaches, short-range weather models become more reliable, typically causing sharper price moves. Unusual heat waves or cold fronts in the weeks prior may also adjust trader expectations for that specific date.