Highest temperature in Busan on July 2?

Prediction market odds often diverge from traditional meteorological forecasts because they incorporate real-time trader sentiment, historical volatility, and broader market dynamics beyond pure weather modeling. While meteorologists rely on atmospheric data and computational models, this market aggregates the collective judgment of traders who may weight recent climate patterns, seasonal anomalies, or geopolitical factors differently. Comparing the implied probability here to official weather service forecasts can reveal where market participants see upside or downside risk relative to expert consensus, offering a complementary perspective on likely outcomes.

On Polymarket, traders set prices by buying and selling shares that represent different temperature outcomes, with the contract price reflecting the probability assigned by the market. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome trades independently, and the spread between bid and ask prices widens or narrows based on liquidity and conviction. As new information emerges—updated forecasts, seasonal data, or real-time weather developments—traders adjust their positions, causing prices to shift and revealing evolving expectations about the highest temperature on the specified date.

This market resolves around Jul 2, 2026, once the event has occurred and the highest temperature in Busan on July 2 is verifiable from credible public reporting. The outcome is determined by comparing actual recorded temperatures against the predefined outcome brackets established at market creation. Traders' positions settle based on which temperature range or specific value is confirmed, with payouts distributed to those who correctly predicted the outcome. Resolution typically follows within hours or days of the event, pending final data confirmation.

Updated weather forecasts and seasonal climate models are primary drivers that shift trader positioning in this market. Major atmospheric patterns—monsoon activity, heat waves, or unexpected cold fronts—can trigger sharp repricing as new data becomes available. Real-time meteorological alerts, historical temperature records for the region, and broader climate anomalies also influence sentiment. Additionally, trading volume spikes and large position changes by informed traders can accelerate price movement, signaling shifting conviction about whether conditions will be hotter or cooler than current consensus expects.