Prediction markets — platforms where users bet real money on future outcomes — are expanding aggressively into weather and climate. Kalshi, a US-based prediction market, reports 500% growth in climate-related wagers over the past year, pushing the market to $1.1bn. It has partnered with the Weather Company, owner of the Weather Channel, to lend credibility to the enterprise. Polymarket is moving in the same direction. The pitch is seductive: harness the "wisdom of crowds" to produce better-calibrated forecasts of climate outcomes. A Kalshi spokesperson frames the company as part of "well-calibrated forecasting data," essentially arguing that money on the line sharpens prediction accuracy. This is the standard prediction-market thesis, borrowed from election and sports betting, now transplanted onto planetary physics. Climate scientists are not buying it. Kaitlyn Trudeau of Climate Central — whose grandfather lost his home in the Los Angeles fires — notes that prediction markets "aren't going to reduce the risks of climate change or solve climate change." The concern is not abstract: large wagers were placed on the LA wildfires before both Kalshi and Polymarket banned wildfire betting due to perverse incentive structures (arson). The platforms are simultaneously claiming forecasting utility and retreating from the categories where stakes are highest. The deeper problem is that climate is not an election. Elections have binary outcomes on fixed dates. Climate is a non-linear system with feedback loops that researchers are still quantifying. A recent study found that natural feedback mechanisms — thawing permafrost, supersized wildfires, overheating wetlands — could accelerate overall global heating by as much as 30%, adding up to 0.4°C to global temperatures. Even the study's authors caution the uncertainties are large. The UN has conceded the 1.5°C target is effectively dead, while the worst-case RCP8.5 pathway is now also unlikely. The confidence interval has narrowed, but the remaining range is enormous. What prediction markets actually do well is aggregate existing sentiment. What they do not do is generate new physical knowledge. A million bettors cannot outperform a climate model on ice-sheet dynamics because the bettors are downstream of the same models and data. The market reflects beliefs about science; it does not replace science. This distinction gets lost when a platform partners with a media brand and frames speculation as "data." The extraction pattern is clear: platforms capture fees and attention from a growing pool of climate-anxious users, while externalizing the moral hazard (wildfire betting) and contributing nothing to mitigation or adaptation. The Weather Company gets a new revenue stream. Bettors get the dopamine hit of engagement with existential risk. The climate itself is unchanged. Meanwhile, the projected El Niño is expected to cause more than 450,000 deaths by February, and planetary boundaries necessary for human flourishing have been "massively breached." The twenty-year question is whether prediction markets evolve into genuinely useful information tools — or whether they remain what they currently are: a financialization layer on top of catastrophe, extracting fees from anxiety while producing no actionable improvement in human response to the crisis.
