Lowest temperature in Washington DC on Jun 14, 2026?

Prediction market odds reflect real-money consensus from traders actively pricing uncertainty, whereas traditional weather forecasts rely on meteorological models and expert analysis. This market allows you to compare crowd-sourced probability estimates against official forecasts from the National Weather Service or other analytical sources. When prediction market odds diverge significantly from published forecasts, it often signals either new information traders are pricing in or a gap between model confidence and market sentiment. Both approaches offer value; markets excel at aggregating dispersed information, while meteorological expertise provides physics-based reasoning.

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, reflecting the probability traders assign to that range occurring. Prices move in real time as new orders flow in, and you can enter limit or market orders to take positions. The platform's matching engine ensures transparent price discovery, with all trades visible in the order history.

This market resolves around Jun 15, 2026, once the lowest temperature recorded in Washington DC on June 14, 2026 is verifiable from credible public sources. The outcome is determined by comparing the final temperature reading against the predefined brackets offered in the market. Once the event occurs and data is confirmed, positions are settled automatically according to which bracket the actual low temperature falls into. All traders holding shares in the winning outcome receive their payout.

Major weather pattern shifts, seasonal forecasts, and atmospheric pressure systems can significantly move this market. Updated climate models or long-range forecasts released closer to June 2026 may shift trader expectations. Unusual heat waves or cold snaps in the preceding weeks could alter baseline assumptions about typical June temperatures in DC. Real-time weather alerts and jet stream changes in early June will likely trigger sharp repricing as the event date nears. Historical temperature data and seasonal anomalies also influence how traders position ahead of the settlement date.