Lowest temperature in Seoul on June 1?

Prediction market odds on Polymarket reflect real-money consensus from traders and often diverge from traditional meteorological forecasts. While weather analysts and climate models provide deterministic temperature ranges based on historical patterns and atmospheric data, prediction markets incorporate broader information—including trader conviction, recent weather trends, and seasonal anomalies. Comparing the implied probability of specific temperature thresholds on Polymarket to official forecasts from Korea Meteorological Administration or similar bodies can reveal whether markets are pricing in more optimistic or pessimistic scenarios than institutional predictions.

On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Polymarket, the lowest temperature in Seoul on June 1 is priced as a set of outcome contracts, each representing a specific temperature range or threshold. Traders buy and sell shares in each outcome, with the price of a share reflecting the market's implied probability that outcome will occur. As new information emerges—weather model updates, seasonal forecasts, or real-time atmospheric conditions—traders adjust their positions, moving prices up or down. The current odds and 24-hour trading volume are visible on the dashboard, showing which temperature ranges attract the most conviction and liquidity.

The market resolves on Jun 1, 2026, after the lowest temperature in Seoul on June 1 has been recorded and verified. Resolution is determined by official meteorological data for Seoul on that date. 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 final reference. Once the outcome is confirmed, the market settles and winning positions are paid out according to their share value.

Several factors can shift odds for Seoul's lowest temperature on June 1. Major weather pattern changes—such as shifts in the East Asian monsoon, tropical cyclone activity, or high-pressure systems—will prompt traders to reprice outcomes. Updated seasonal forecasts from meteorological agencies and real-time atmospheric data releases can trigger significant moves. Anomalous global climate events or El Niño/La Niña developments may also influence regional temperature expectations. As June 1 approaches, actual early-June weather observations and short-range model forecasts will become increasingly influential, driving late-stage trading activity and odds adjustments.