"In many ways, the changes farmers are experiencing are completely in line with what climate models predicted, so the overall impact should not be a surprise," said study co-author Stefania Di Tommaso, a research data analyst at FSE.
An unexpected twist: Climate models largely failed to predict the scale of drying in temperate zones like Europe and China. Observed increases in air dryness were far greater than projections had indicated for these regions. By contrast, U.S. farms, especially in the Midwest, experienced far less warming and drying than expected.
"These two big surprises are important to resolve," said Di Tommaso. "Of all the uncertainties in climate models, these are the two big ones that matter for global food production."
The authors note that model errors do not only matter for predicting impacts, but also for designing adaptations. Past efforts to extend growing seasons with longer-maturing crop varieties, for example, may have missed the mark because models didn't fully capture the drying trends that now threaten those very strategies.
The findings echo concerns raised in a study published in March that found U.S. agricultural productivity could slow dramatically in coming decades without major investment in climate adaptation. Taken together, the studies highlight a growing need for more accurate modeling and smarter adaptation strategies.
"Overall, I think climate science has done a remarkable job of anticipating global impacts on the main grains, and we should continue to rely on this science to guide policy decisions," said Lobell. "If anything, I think the blind spots have been on specialized crops where we don't have as much modeling, but which are very salient to consumers.
"That includes things like coffee, cocoa, oranges, and olives. All these have been seeing supply challenges and price increases. These matter less for food security but may be more eye-catching for consumers who might not otherwise care about climate change."
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