On May 19, 2026, Manila's weather will provide a natural test of how prediction markets process environmental information. This collection of markets focuses on a single measurable outcome: the highest temperature the city will reach that day. Rather than a single yes-or-no question, you'll find a spectrum of related markets covering temperatures from below 29°C through 39°C and above, plus several markets pinpointing exact temperature values like 30°C, 31°C, and 37°C. This structure mirrors how weather analysis works in practice—forecasters don't just predict "hot" or "not hot," but rather examine probability distributions across specific temperature ranges. Each market here represents a distinct possibility, and together they form a complete picture of what traders and forecasters expect. When examining these prices, you're observing a probability spectrum in real time. Lower prices indicate outcomes the market views as less likely, while higher prices suggest stronger consensus around those conditions. By comparing the prices across different thresholds—say, the market for 29°C or below versus the one for 39°C or higher—you can read what the collective forecast looks like. The distribution of prices across all five markets implicitly reveals where forecasters expect the temperature to most likely fall. Because this resolution date is just days away, these prices aren't abstract speculation but rather reflect genuine atmospheric patterns and meteorological forecasts. The tight time horizon makes Manila's May 19 temperature an ideal lens through which to understand prediction markets: they're instruments for aggregating distributed knowledge about measurable, near-term outcomes.