Highest temperature in Wuhan on July 13?

Prediction market odds reflect aggregated trader expectations and often incorporate meteorological models, historical weather patterns, and real-time atmospheric data. Traditional weather analysts and forecasters typically rely on numerical weather prediction models and satellite imagery to estimate temperature ranges. This market allows traders to express confidence in specific temperature thresholds, which can diverge from or align with official forecasts depending on how traders weight recent data and model uncertainty. Comparing market-implied probabilities to published forecasts from meteorological agencies offers insight into whether traders are pricing in more or less extreme outcomes than institutional experts.

On Polymarket, this market is priced through an automated market maker mechanism where traders buy and sell shares corresponding to different temperature outcomes. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The current odds reflect the collective bets of all participants; as traders buy shares predicting higher or lower temperatures, the price adjusts to balance supply and demand. Each outcome has an associated probability derived from its share price, allowing traders to see the implied likelihood of the highest temperature reaching specific thresholds on July 13. Real-time price discovery ensures the market continuously reprices as new information becomes available.

This market resolves around Jul 13, 2026, once the event has occurred and the highest temperature in Wuhan on July 13 can be verified against credible public sources. The outcome is determined by comparing actual recorded temperatures to the specific thresholds defined in the market's outcome options. Resolution typically occurs within hours or a day after the event date, once official meteorological data is published and confirmed. Traders' positions settle based on which outcome occurred, with winnings distributed to those who correctly predicted the temperature range.

Weather model updates and forecasts from meteorological agencies can significantly shift trader expectations and move odds in this market. Seasonal weather patterns, atmospheric pressure systems, and any unusual climate anomalies reported in the weeks leading up to July 13 may influence trading activity. Real-time satellite imagery and short-range forecasts released closer to the event date typically drive the most dramatic repricing. Major weather events or heat waves affecting the region could also prompt traders to adjust positions, as could any revisions to historical temperature records or measurement methodologies that affect baseline expectations for Wuhan's typical July temperatures.