Highest temperature in Tokyo on June 4?

Prediction market odds on Polymarket reflect real-money consensus from traders worldwide, while analyst forecasts come from meteorological agencies and climate models. Markets often price in broader uncertainty and tail risks that traditional forecasts may underweight. Comparing the market's implied temperature distribution to Japan Meteorological Agency seasonal outlooks or long-range weather models can reveal where traders see divergence from official guidance. This gap often signals either market skepticism of analyst confidence or emerging data that hasn't yet shifted institutional forecasts.

On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Polymarket, the Highest temperature in Tokyo on June 4 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 prices reflecting the collective probability assigned by the market. As new weather data, seasonal patterns, or climate signals emerge, traders adjust positions, moving prices up or down. The contract price directly translates to implied probability, allowing you to see exactly what the market believes about the likelihood of each temperature outcome.

The market resolves on Jun 4, 2026, after June 4 has concluded and the actual highest temperature in Tokyo is recorded. Resolution is determined by official temperature data from a designated meteorological source, ensuring an objective, verifiable outcome. Once the final temperature is confirmed, the contract corresponding to the correct outcome is settled at full value, and all other contracts expire worthless. Traders holding the winning outcome receive their payout based on the price at which they held their position.

Major weather pattern shifts, updated seasonal forecasts, and atmospheric anomalies can significantly move odds. Early June typhoon activity, changes in the Pacific jet stream, or unexpected heat waves across East Asia may trigger repricing. Historical temperature records for early June in Tokyo provide a baseline; deviations from typical patterns often spark trader repositioning. Real-time weather model updates, especially from high-resolution ensemble forecasts, frequently drive short-term volatility. Climate oscillations like the Pacific Decadal Oscillation or El Niño phase can also influence longer-term expectations as the event date approaches.