Weather and Climate Data Signals
Weather and climate data — temperature, rainfall, storm tracks — are used as alternative-data signals for sectors whose demand or supply is directly weather-sensitive, like energy, agriculture, and insurance.
Weather directly drives demand and supply in several markets: natural gas and electricity demand rise sharply in unusually cold winters or hot summers as heating and cooling use spikes, crop yields depend heavily on rainfall and temperature during specific growing-season windows, and hurricane paths affect both energy infrastructure and insurance losses. Because forecasts and historical weather records are publicly available at fine geographic and time resolution, they've long been used as a trading signal for commodities, utilities, agriculture, and insurance-linked securities.
The signal's edge typically comes from combining weather data with a model of exposure — knowing that a cold snap is coming matters less than knowing which specific regions have the most gas-heated homes, or which crop-growing areas are experiencing an unusual drought at a moisture-sensitive growth stage. Forecasts also decay in value quickly: a 10-day-ahead forecast is far less certain than a 2-day-ahead one, so the tradeable edge is often concentrated in the days just before an event, once forecast uncertainty narrows enough to act on.
For example, a trader watching an unusually cold forecast for the U.S. Midwest two weeks before a natural gas storage report might expect higher-than-average heating demand to show up as a larger-than-usual draw on gas inventories, and take a position ahead of the report accordingly.
Weather data is most useful as a trading signal when paired with a model of exactly which markets and regions are exposed to it — the raw temperature or rainfall number matters far less than knowing where and how it translates into real supply or demand.