Highest temperature in Guangzhou on June 14?

Prediction market prices often diverge from traditional weather forecasts because they incorporate real-time trader sentiment and financial incentives alongside meteorological models. While professional meteorologists issue point estimates or ranges based on atmospheric data, this market aggregates the beliefs of many participants who profit or lose based on accuracy. Comparing the implied temperature range from current odds to published forecasts from national weather services can reveal where traders expect conditions to differ from baseline models, though both sources ultimately depend on the same underlying atmospheric conditions.

On Polymarket, traders set prices by buying and selling shares in discrete temperature outcome brackets for Guangzhou on June 14. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome contract trades independently, and the sum of all outcome prices reflects the market's total confidence. Prices move as new information arrives—such as updated weather models or seasonal patterns—and traders arbitrage between outcomes to lock in perceived mispricings. The platform's automated market maker ensures continuous liquidity, allowing you to enter or exit positions at transparent, real-time rates.

This market resolves around Jun 14, 2026, once the highest temperature recorded in Guangzhou on June 14 is verifiable from credible public sources. The outcome is determined by the actual meteorological data reported for that date, typically from official weather stations or national meteorological agencies. Winning shares are those corresponding to the temperature bracket that encompasses the final recorded high, and all other shares expire worthless. Resolution occurs shortly after the close of the trading day on June 14.

Major weather pattern shifts—such as tropical systems, monsoon onset, or heat waves—can significantly alter odds in this market. Updated seasonal forecasts, real-time atmospheric models, and historical temperature anomalies for early June all influence trader positioning. Short-term catalysts include official meteorological advisories, satellite imagery showing cloud cover or pressure systems, and any unusual heat or cold events in the region weeks before June 14. As the date approaches, intraday weather updates and overnight model runs typically drive the most volatile price swings.