Highest temperature in Seoul on June 28?

Prediction market odds reflect the aggregated beliefs of traders betting real money, whereas traditional weather analysts rely on numerical models and historical data. This market often incorporates faster-moving information—such as updated satellite imagery or sudden weather pattern shifts—than formal forecasts released days in advance. Comparing this market's implied probabilities to published meteorological outlooks can reveal where professional consensus and trader sentiment diverge. Both sources have merit: analysts bring domain expertise, while markets reward accurate pricing through financial incentives.

On Polymarket, traders set prices by buying and selling outcome contracts through an automated market maker. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each contract represents a specific temperature range or threshold, and its price reflects the collective probability traders assign to that outcome occurring. When demand for a particular temperature scenario rises, that contract's price increases; conversely, selling pressure lowers it. The spread between bid and ask prices tightens as more liquidity enters the market, making it cheaper to trade in and out of positions.

This market resolves around Jun 28, 2026, once Seoul's highest temperature for June 28 is verifiable from credible public reporting. The outcome is determined by comparing actual recorded temperatures against the contract thresholds defined at market creation. Resolution typically occurs within hours or a day after the event, once official meteorological data becomes available. Traders holding contracts aligned with the verified temperature will receive payouts proportional to their holdings.

Updated weather forecasts from major meteorological agencies can shift odds significantly, especially if models show a sudden warming or cooling trend. Seasonal climate patterns—such as early monsoon activity or heat waves—may trigger repricing as traders adjust expectations. Real-time atmospheric data, including pressure systems and humidity readings, often influences short-term price swings. Major weather events in adjacent regions or unexpected shifts in jet stream positioning can also move this market as traders incorporate new information into their probability estimates.