On May 5, Beijing's maximum temperature will be the focus of this prediction market cluster. The three markets below each represent a specific temperature threshold—35°C, 36°C, and 37°C—allowing you to isolate probability estimates across a narrow range of possible daily highs. This granular outcome structure is typical in weather prediction markets, where even single-degree differences can reflect meaningful distinctions in expected conditions. Unlike a simple binary forecast, these three related markets let you express nuanced views: you might be confident the high will reach 36°C but uncertain whether it will climb further to 37°C, or conversely, you might see a lower probability of reaching even 35°C. The prices across these outcomes follow an implicit ordering rooted in probability theory—in well-functioning markets, the likelihood of hitting 35°C should exceed that of 36°C, which should exceed that of 37°C, since each higher threshold is a subset of the possibilities below it. As you review the real-time prices, they represent the market's collective probability assessment for each outcome. When examining related markets like these, pay attention to the spacing between prices and any deviations from the expected pattern—unusual spreads often signal areas of genuine disagreement or where new information is shifting expectations. The prices you see incorporate weather forecasts, historical climate patterns, and any breaking meteorological updates relevant to that date. In this way, prediction markets serve as a real-time aggregation of dispersed information about Beijing's weather, condensing multiple sources of data and expert opinion into a single price for each outcome.