Lowest temperature in Shanghai on June 13?

Prediction market odds on Polymarket reflect real-money bets from traders worldwide and often diverge from traditional meteorological forecasts. While weather analysts publish point estimates and confidence intervals based on climate models, prediction markets aggregate distributed information from participants with financial incentives to be accurate. Comparing Polymarket odds to official Shanghai weather bureau forecasts or third-party meteorological models can reveal whether markets are pricing in more optimistic or pessimistic temperature scenarios than experts predict.

On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Polymarket, this event is priced through outcome tokens representing specific temperature ranges or thresholds for Shanghai's low on June 13. Traders buy and sell these tokens at prices reflecting the probability of each outcome. The current market price of each outcome token directly indicates the crowd's belief in that temperature scenario. As new weather data emerges or the event date approaches, token prices adjust dynamically based on order flow and trader positioning.

The market resolves on Jun 13, 2026, after June 13 concludes in Shanghai. Resolution is determined by the actual lowest temperature recorded in Shanghai on that date. Official meteorological data sources are used to verify the outcome and settle all positions. Traders should monitor the specified data source and resolution criteria outlined in the market terms to understand which temperature reading will be used as the authoritative reference for settlement.

Several factors can shift odds for Shanghai's June 13 low temperature. Major weather pattern changes, updated seasonal forecasts, or tropical cyclone activity in East Asia could significantly move the market. Real-time atmospheric pressure systems, ocean temperature anomalies, and monsoon intensity reports may trigger repricing. As June approaches, daily weather model updates become more precise and influential. Additionally, historical temperature records for mid-June in Shanghai and broader climate trends could influence trader positioning and market probability estimates.