Lowest temperature in New York City on Jun 6, 2026?

Prediction market odds on Kalshi reflect real-money trader expectations for the lowest temperature on June 6, 2026, and often diverge from traditional meteorological forecasts issued by the National Weather Service or private weather services. While meteorologists rely on numerical weather models and historical climate data, prediction markets incorporate trader beliefs about model accuracy, potential forecast revisions, and tail-risk scenarios. Comparing Kalshi odds to published seasonal outlooks or ensemble forecasts can reveal whether markets are pricing in more extreme cold or warmth than consensus weather models suggest.

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 June 6, 2026, in New York City is priced as a set of binary or range-based contracts corresponding to specific temperature thresholds. Traders buy or sell shares reflecting their belief about whether the actual low will fall above or below those strike levels. Kalshi's order book displays bid-ask spreads for each contract, and prices update continuously as new trades execute. The implied probability of each outcome is derived from the current contract price, allowing traders to quickly assess market consensus on the likelihood of various temperature scenarios.

The market resolves on Jun 7, 2026, after the close of trading and once the official lowest temperature reading for June 6, 2026, in New York City is recorded. Resolution timing allows for final data verification and ensures all trades are settled based on the definitive temperature measurement. Traders should monitor the event page for any updates to resolution criteria or data sources as the date approaches, and confirm their positions well before the end date to avoid last-minute settlement surprises.

Major weather pattern shifts, updated seasonal forecasts, and real-time atmospheric data releases can significantly move odds for the June 6 low temperature in New York City. Traders monitor extended-range weather models, jet stream positioning, and large-scale climate oscillations like the North Atlantic Oscillation to anticipate cold or warm anomalies. As June approaches, short-range forecasts become more reliable, typically causing sharper price moves. Unexpected polar vortex disruptions, tropical activity, or sudden model consensus changes can trigger rapid repricing on Kalshi, so active traders watch meteorological updates closely.