The past six years have seen three years of exceedingly poor weather conditions for farmers, followed by three far more favourable years that have helped crops bounce back with a vengeance. Corey Cherr, the head of agriculture and weather research and forecasts at Thomson Reuters, has tracked and analyzed their cumulative effect on crops worldwide using satellite imagery and remote sensing, among other data points.
“We’ve had a lot of synchronous swings in weather that had been almost worldwide,” Cherr said. From 2010 to 2012, “every time you turned around there was a drought somewhere, devastating crop production,” he said.
From 2013 through to the present, though, Cherr and his team observed “three years of the opposite, which has helped to mitigate some of the warming that we’d been seeing in temperatures.”
In both cases, satellite imagery was a boon for Cherr’s team. During the drought years, the disruptive technology helped to confirm early on that the weather was exceptionally extreme, and gave advance warning to people in the market that “the destruction was a lot worse than the consensus was expecting.” During the following years of cooler temperatures and much-needed rainfall, the imagery confirmed the crops were performing far better than expected. “We’ve had very burdensome supplies that have actually been much more than the market expected, and the satellite data has helped us understand that,” Cherr said.
Disruptive technology: Forewarned is forearmed
Satellite imagery is one of the tools Cherr and his team use to make more accurate and longer-range weather forecasts. Their work, highlighted in Thomson Reuters Nine Billion Bowls report, also involves ground-level crop reporting, data resources and expert analysis. The goal is to be able to let farmers and commodity professionals know in advance what kind of weather the coming seasons may bring, to help them get ahead of any extreme effects.
“Satellite data is incredibly useful because some of it has global coverage and relatively frequent and reliable update periods,” Cherr said. “And we have in some cases a long enough history where we can explore and test the data for objective relationships.”
Objective relationships occur when data shows a pattern of some kind — for example the health of a crop at a given point in the year — recurring consistently over time. Cherr’s team uses the satellite data and historical models to “confirm or reject the effects we think the weather should be having.” Satellite data has an additional use for Cherr and his team: it is able to demonstrate how farmers are gradually changing their management. “We can see changes in things like when farmers plant crops and how quickly crops grow and are harvested and replanted,” he said.
Busts versus bumper crops in South America
These charts show the extreme contrast in satellite imagery and field observations between an exceptionally strong drought (2011/12), in which approximately 25% of the soybean crop in southern Brazil and Argentina was lost, and perhaps the most favorable season of recent decades (2014/15), in which wet weather raised production 10% to 15% above normal across southern Brazil and central Argentina.
Rather than being hit when it’s too late to react, the ability to see these patterns in advance helps farmers decide what to plant, how much, and when to send it to market – a win-win for farmers and the food supply chain.
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