These six linked prediction markets focus on a single weather event: the maximum temperature in Seoul on May 17, 2026. Rather than a simple yes-or-no question, this cluster of markets breaks down the possible outcome into specific temperature points and thresholds, allowing participants to express nuanced forecasts across a granular range. Whether you expect Seoul to experience a cool spring day at 16°C or below, or a warmer afternoon reaching 20°C, there is a market corresponding to your expectation. By monitoring these markets together, you can observe how participants distribute their confidence across different temperature scenarios—revealing where the consensus median falls and where the market perceives the most uncertainty. The relative prices across these markets tell an important story: if markets predicting cooler temperatures (16°C or below) command higher prices than those predicting warmer conditions (19–20°C), it suggests participants collectively expect Seoul to experience a cooler day. Conversely, strong prices in the higher-temperature markets suggest warmer-than-normal conditions are anticipated. Because each market addresses the same underlying variable, watching their price movements together provides richer insight into forecast distribution than any single question could deliver. This structure is particularly valuable for decision-makers who need to understand not just directional expectations but the full range of plausible outcomes. As May 17 approaches, these prices will converge toward reality: when Seoul's actual maximum temperature is recorded, the markets that correctly captured the outcome will be confirmed, and prices will reflect complete certainty about what actually occurred.