Lowest temperature in Seoul on June 19?

Prediction market odds often diverge from traditional meteorological forecasts because they incorporate real-time trader sentiment, historical volatility, and broader risk assessments beyond raw model outputs. While weather analysts rely on numerical weather prediction systems and historical climate data for Seoul in mid-June, this market aggregates diverse participant views into a single probability. Comparing the two reveals whether traders are pricing in tail risks or seasonal anomalies that conventional forecasts may underweight or overlook.

On Polymarket, traders set prices through an automated market maker that adjusts odds based on buy and sell pressure across temperature outcome brackets. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each contract share represents a specific temperature range, and the cost to purchase a share reflects the implied probability of that outcome occurring. As new information surfaces—such as updated seasonal forecasts or atmospheric patterns—traders adjust their positions, causing prices to shift dynamically until the market closes on Jun 19, 2026.

This market resolves around Jun 19, 2026, once the lowest temperature recorded in Seoul on June 19 is verifiable from credible public sources. The outcome is determined by comparing the actual minimum temperature reading against the predefined outcome brackets established at market creation. Resolution occurs after the trading window closes and the final temperature data is confirmed, at which point winning shares are paid out according to the bracket that contains the verified low.

Major weather pattern shifts, tropical storm activity, or unexpected atmospheric blocking systems could significantly alter temperature expectations for Seoul in mid-June. Updated seasonal forecasts from meteorological agencies, historical precedent for extreme heat or cold in that region, and real-time atmospheric data releases will influence trader positioning. Additionally, broader climate anomalies or El Niño/La Niña developments may shift long-range outlooks, causing sharp repricing as the event date approaches and uncertainty narrows.