Most people view these markets as if they were playing a guessing game, such as "Will they be warmer or colder?" or "Which range will they fall into But the climate market can actually be broken down like a quantitative problem: NASA data ->benchmark model ->probability distribution ->comparison of event prediction (EV) and Polymarket prices. And this is precisely the interesting thing: linear regression itself does not constitute an advantage, it is only the lowest benchmark, demonstrating how the market should think if only looking at long-term trends. The true excess return (Alpha) begins after this: who can better adjust the benchmark through ENSO (El Ni ñ o-Southern Oscillation), who can obtain the latest ERA5 data faster, who can more accurately estimate the residual cooling after La Ni ñ a, and who will not blindly buy a certain range just because it looks very likely. Therefore, the question is not 'Will April be hot?', but 'How far is the current Polymarket price from the fair probability after completing all corrections?'? ”That's why these markets are so fascinating: from the outside, they may seem dull and boring, but at their core, it's a pure game about data, speed, and model quality.