Most people look at these markets like they're playing a guessing game, like 'Will it be warmer or colder?' or 'Which range will it fall into?' But climate markets can actually be broken down like a quantitative problem: NASA data → baseline models → probability distributions → event predictions (EV) compared to Polymarket prices. And that's where the fun begins: linear regression itself doesn’t create an edge—it’s just the bare minimum benchmark, showing how the market should think if it only considers long-term trends. The real alpha starts after that: who can better adjust the baseline using ENSO (El Niño-Southern Oscillation), who can access the latest ERA5 data faster, who can more accurately estimate the residual cooling after La Niña, and who won’t blindly buy into a range just because 'it looks likely.' So, the question isn’t 'Will April be hot?' but rather 'After all adjustments, how far is the current Polymarket price from the fair probability?' That’s why these markets are so fascinating: from the outside, they seem dull and boring, but at their core, they’re a pure game of data, speed, and model quality.