Highest temperature in Singapore on June 17?

Prediction market odds often diverge from traditional meteorological forecasts because traders incorporate real-time data, historical patterns, and their own risk assessments into prices. While weather analysts publish deterministic point forecasts or confidence intervals based on numerical models, this market reflects the aggregated belief of participants who have financial incentive to be accurate. Comparing the leading outcome odds to published forecasts from Singapore's meteorological authority can reveal whether traders are pricing in more or less uncertainty than official models suggest, offering a complementary perspective on temperature expectations.

On Polymarket, traders set prices through an automated market maker that converts buy and sell orders into real-time odds for each temperature outcome. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The cost to buy a share reflects the current probability assigned by the market; as new information arrives or trader sentiment shifts, prices adjust dynamically. Liquidity and trading volume directly influence how quickly prices move and how tight the spreads are between bid and ask, so higher activity typically means more efficient price discovery for temperature predictions.

This market resolves around Jun 17, 2026, once the highest temperature recorded in Singapore on June 17 becomes verifiable from credible public sources. The outcome is determined by comparing trader predictions against the official recorded temperature for that date, with the winning outcome paying out based on which threshold bracket the actual reading falls into. Resolution occurs after the event concludes and data is confirmed, ensuring all participants have access to the same authoritative information.

Temperature predictions can shift based on updated weather models, seasonal climate patterns, and real-time atmospheric conditions as June 17 approaches. Major weather systems, monsoon activity, or unusual heat events in the region could trigger significant repricing. Additionally, historical temperature records for that date and broader climate trends may influence trader positioning. As the event date draws closer, intraday weather updates and satellite data typically drive increased trading activity and volatility in this market.