ClimateLens 2.0 is Here → See what’s new
Andy Paterson • April 28th, 2026.
Six months before Brazilian coffee prices spiked 10%, ClimateAi flagged the risk with 69% confidence. One procurement team acted early, saving $3 million.
Many agricultural and food companies still make decisions based on 7-day forecasts, but by the time the event is a week out, most opportunities to act have passed.
To enable decision-makers with the information they need to take the actions required to achieve impactful savings and mitigate losses, accurate long-term forecasts are essential. Here is why.
Knowing that an extreme bout of precipitation, a frost event, or extreme heat will occur 7 days before it happens is helpful. But the opportunity to take the kind of action that would prevent significant damage has already passed.
So while public forecasts stop at 7–14 days, climate projections extend out to 6 months, which is where key decisions can save millions.
An accurate forecast months before events happen can help both buyers and producers save millions and build a competitive advantage through better decision-making. It enables:
These long lead times are not only good for agricultural companies. When we helped a roofing company predict 2022’s Hurricane Ian in Florida months in advance, it enabled the company to pre-position supplies and secure $15 million in additional sales.
The closer an event gets, the more accurate the forecasts will be, but 90-100% probability doesn’t matter if it’s too late to act.
A probability forecast of 60–75% accuracy at 6 months is much more useful. The comparison isn’t 60% vs. 90%, it’s 60% signal vs. 0% signal. Even a directional forecast at 6 months lets you hedge, adjust, and position.
Reactive decisions made after the damage hits cost significantly more than proactive ones made with imperfect early information.
The ROI of a long-range forecast isn’t about a perfect decision based on 100% accuracy. It’s more about improving decisions based on better information before its too late.
A simple way to estimate that value is: Value = Impact × Probability × Frequency
In practice, that comes down to three questions:
Multiply those together to get a baseline estimate of your annual exposure. From there, the math becomes simple: if a 6-month forecast helps you make just one better decision, buying earlier, shifting sourcing, or adjusting timing, it can offset its cost in a single event.
Studies have shown that the longer out an accurate forecast comes, the more companies can save assets and make better decisions.
As climate change adapts seasonal timing and makes weather more erratic, companies need to be more adaptable and informed. Long-range weather forecasting ensures they have the information they need to make adaptation decisions way before an event happens.
See how ClimateAi’s 6-month forecasts apply to your supply chain decisions.
Long-range (sub-seasonal to seasonal) forecasts are typically 60–75% accurate, depending on the region, crop, and weather variable. While this is lower than short-term forecasts, the added lead time allows businesses to act earlier, which is often more valuable than higher accuracy closer to the event.
Most high-impact agricultural and supply chain decisions happen well before a 14-day window, including: Commodity procurement and hedging, planting and harvest timing, supplier and region selection, and inventory and logistics planning. By the time a 7–14 day forecast signals a risk, many of these decisions are already locked in.
Long-range forecasts give companies time to adjust before disruption occurs. This can include sourcing from alternative regions, securing supply early, or adjusting production plans. Instead of reacting to shortages or price spikes, companies can reduce exposure and protect margins.
Companies use long-range forecasts to make earlier, higher-impact decisions, such as Buying commodities before price increases, adjusting planting schedules to avoid stress periods, shifting sourcing to lower-risk regions, and planning logistics and inventory ahead of disruptions. In many cases, acting early on a probabilistic forecast can create a measurable financial advantage.
Start by estimating your exposure to weather-related risk: identify your most climate-sensitive cost or revenue line, estimate the financial impact of a bad season, and consider how often it occurs. If earlier insight helps improve even one major decision, the value often outweighs the cost of the forecast.
Andy Paterson is a content creator and strategist at ClimateAi. Before joining the team, he was a content leader at various climate and sustainability start-ups and enterprises.
Andy has held writing, content strategy, and editing roles at BCG, Persefoni, and Good.Lab. He has helped build one of the industry’s most popular newsletters and regularly publishes environmental science articles with Research Publishing.