Lowest temperature in Washington DC on Jun 24, 2026?

Prediction market odds on this market reflect real-money incentives that often diverge from traditional weather analyst forecasts. While meteorologists issue point estimates and confidence intervals based on numerical models, traders price outcomes by aggregating dispersed information and personal conviction. Markets tend to incorporate late-breaking data and adjust faster than published forecasts when new atmospheric patterns emerge. Comparing this market's odds to seasonal climate outlooks or National Weather Service guidance can reveal where traders expect conditions to deviate from consensus models, offering a complementary perspective on June temperature expectations for the DC region.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to different temperature ranges for June 24, 2026. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Share prices reflect the collective probability assigned to each outcome band, with tighter spreads indicating higher confidence and wider spreads suggesting uncertainty. As new weather data or seasonal patterns become available, traders adjust their bids and asks, causing prices to move. The platform's matching engine executes trades at the best available price, ensuring transparent price discovery throughout the market's duration.

This market resolves around Jun 25, 2026, after June 24, 2026 has passed and the day's low temperature for Washington DC is recorded. The outcome is confirmed once the actual low temperature is verifiable from credible public sources. Traders holding shares in the correct outcome range receive their payout, while incorrect positions expire worthless. Resolution occurs automatically once the data is finalized, allowing participants to settle their positions and see final results.

Several factors could shift odds in this market significantly. Updated seasonal climate outlooks and long-range weather models released by meteorological agencies often trigger repricing as traders adjust for shifting atmospheric patterns. Major weather events or anomalies in the months preceding June 2026 may influence expectations for that specific date. El Niño or La Niña conditions, solar activity, and other climate oscillations can alter temperature probabilities. Additionally, as June 24 approaches, short-range forecasts become more precise, typically narrowing the range of likely outcomes and concentrating trading volume around the most probable temperature bands.