On May 18, Hong Kong's weather becomes the subject of three interconnected prediction markets that together offer a granular snapshot of how traders assess the city's high temperature. These markets segment the outcome space into three specific scenarios—21°C or below, exactly 22°C, or exactly 23°C—rather than treating temperature as a simple binary choice. This outcome-specific structure captures the probability distribution across a critical range, reflecting how expectations shift with subtle changes in atmospheric conditions and forecasting data. By comparing prices across the three markets, you can observe how the collective trader base distributes its confidence: lower prices on extreme outcomes (21°C or below) versus central outcomes (22°C) might signal confidence in modest warming, while patterns skewed toward higher temperatures could suggest unusual weather pressures or disagreement among forecasting models. As new meteorological data, satellite imagery, and professional forecasts arrive throughout May, these prices update in real time, providing a continuous market-derived estimate of the weather outcome. The fine-grained outcome structure rewards careful attention to weather detail and allows participants to express precise views aligned with their forecasting models or domain expertise. Whether you're tracking climate patterns, testing prediction models, or curious about subtropical weather dynamics, these grouped markets offer transparent, real-time insights into collective expectations for Hong Kong's late-spring weather.