Highest temperature in Guangzhou on June 27?

Prediction market odds reflect real-money trader conviction and often incorporate meteorological forecasts, historical climate patterns, and seasonal trends faster than traditional analyst models update. While weather agencies publish point forecasts and confidence intervals, this market prices uncertainty through continuous trading. Comparing the implied probability here to official forecasts can reveal where traders see asymmetric risk—for instance, if the market prices a higher chance of extreme heat than meteorologists expect, it may signal traders are weighing tail risks or recent model updates more heavily.

On Polymarket, traders set prices by buying and selling shares corresponding to different temperature outcomes. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome contract trades independently, with the price of a share reflecting the collective probability traders assign to that temperature range occurring. As new information arrives—updated forecasts, seasonal patterns, or real-time atmospheric data—traders adjust their positions, moving prices up or down to reflect changing expectations about the highest temperature on the specified date.

This market resolves around Jun 27, 2026, once the highest temperature recorded in Guangzhou on June 27 is verifiable from credible public sources. The outcome is determined by comparing the actual peak temperature against the predefined ranges offered in the market. Traders holding shares in the correct outcome receive their payout, while incorrect positions expire worthless. Resolution typically occurs within hours of the close of the trading day once official temperature data is published.

Major weather pattern shifts, updated seasonal forecasts, and real-time atmospheric conditions will drive significant price movement in this market. Tropical systems, monsoon onset timing, or unexpected heat waves in the region can trigger rapid repricing. Additionally, historical temperature anomalies, urban heat island effects, and climate oscillations like El Niño or La Niña influence trader expectations. As June 27 approaches, intraday weather updates and short-range model consensus will likely create the most volatile trading activity, especially in the final 48 hours before resolution.