Lowest temperature in Washington DC on Jun 4, 2026?

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the lowest temperature outcome for Washington DC on June 4, 2026, is priced as binary or range-based contracts reflecting discrete temperature thresholds. Traders buy and sell shares corresponding to whether the actual low will fall within or outside specified bands. Pricing reflects the collective probability assessment of all active traders, updated in real time as new weather models, historical analogues, and seasonal data become available. Kalshi's order book displays bid-ask spreads that tighten as the event date approaches and forecasts solidify, allowing you to enter or exit positions at market or limit prices.

The market resolves on Jun 5, 2026, after the close of June 4, 2026, in Washington DC. Resolution is determined by the official lowest temperature recorded on that date, sourced from designated weather stations or meteorological authorities. Once the actual minimum temperature is confirmed and published, the contract settles according to which outcome bracket or threshold the recorded value matches. Traders holding positions aligned with the resolved outcome receive their winnings, while opposing positions expire worthless. The resolution process is automated once the official data is available.

Several factors can shift market odds before June 4, 2026. Updated long-range weather models from NOAA or international meteorological centers may indicate stronger or weaker cold air advection. Seasonal climate patterns, such as La Niña or high-pressure systems, influence early-summer temperatures in the Mid-Atlantic. Historical analogue years with similar atmospheric setups provide traders with reference points. As June approaches, medium-range forecasts become more precise, typically narrowing the range of plausible outcomes. Real-time atmospheric data, jet-stream positioning, and any unusual weather events in preceding weeks will drive incremental repricing on Kalshi.