Highest temperature in Seoul on July 13?

Prediction markets like this one aggregate trader expectations into live odds that often reflect real-time consensus differently than traditional weather forecasts. While meteorologists publish point estimates and confidence intervals based on atmospheric models, traders in this market price outcomes based on collective belief about the highest temperature Seoul will reach on July 13. The two approaches can diverge when new data emerges or when traders weigh uncertainty differently than model outputs suggest. Comparing the market's implied probability to official forecasts reveals whether traders are more bullish or bearish than experts on extreme heat.

On Polymarket, this market is priced through an automated market maker that converts trader orders into real-time odds for each outcome. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Traders buy and sell shares representing different temperature ranges, and the platform's pricing algorithm adjusts odds based on order flow and liquidity. Higher trading volume typically narrows the spread between bid and ask prices, making it easier to enter and exit positions. The top outcome currently reflects market consensus, though prices remain dynamic as new information and trader activity reshape expectations.

This market resolves around Jul 13, 2026, once the highest temperature recorded in Seoul on July 13 is verifiable from credible public sources. The outcome is determined by comparing actual weather data against the temperature thresholds embedded in each market option. Traders who correctly predicted the final temperature range receive their winnings, while incorrect positions expire worthless. Resolution typically occurs within hours of the market end date, once official meteorological records are published and confirmed.

Several factors can shift odds in this market before it closes. Updated weather models and seasonal forecasts published by meteorological agencies often trigger repricing as traders adjust to new data. Major atmospheric patterns—such as high-pressure systems, monsoon activity, or heat waves affecting East Asia—can reshape expectations for Seoul's peak temperature. Real-time weather alerts and overnight model runs may cause sharp moves in the final days. Additionally, trader sentiment and media coverage of extreme weather events can amplify volatility, especially if comparable heat records are set elsewhere in the region.