Highest temperature in Shanghai on June 28?

Prediction market odds often diverge from traditional meteorological forecasts because they incorporate real-time trader behavior, uncertainty premiums, and collective intelligence beyond a single model. While weather analysts rely on physics-based simulations and historical data, this market aggregates the views of many participants with varying risk tolerances and information access. The odds can shift rapidly if new satellite imagery, atmospheric pressure readings, or seasonal patterns emerge. Comparing the market's implied probability to official forecasts from meteorological agencies reveals whether traders are pricing in more or less extreme outcomes than experts currently project.

On Polymarket, traders set the odds through an automated market maker that adjusts prices based on buy and sell pressure. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each contract represents a specific temperature outcome—such as whether the high will reach 24°C—and the price reflects the collective probability estimate. As traders place bets, the price moves up or down, incentivizing arbitrage and information discovery. The more capital flowing into a particular outcome, the higher its price climbs, creating a dynamic equilibrium that balances supply and demand in real time.

This market resolves around Jun 28, 2026, once the highest temperature recorded in Shanghai on that date becomes verifiable from credible public sources. The outcome is determined by official meteorological data, typically published by China's national weather service or recognized international weather databases. Resolution occurs after the trading window closes and the final temperature reading is confirmed. Traders must wait for this official confirmation before payouts are distributed to those holding the winning contract.

Major weather pattern shifts, tropical cyclone activity, or unexpected atmospheric blocking systems could significantly alter temperature expectations for Shanghai in late June. Updated seasonal forecasts, El Niño or La Niña developments, and real-time satellite data all influence trader positioning. Urban heat island effects and local pollution levels may also factor into market repricing. Additionally, any revision to historical temperature records or changes in measurement methodology could trigger recalibration of odds as traders reassess baseline conditions and precedent.