The researchers entered various scenarios into their computer models to simulate the effects of elevated carbon dioxide (CO2) in the atmosphere on cotton crop yields. If CO2 emissions increase at their present rate, many scientists believe that the atmospheric concentrations of greenhouse gases are likely to double compared to pre-industrial levels by the year 2060.
Along with climate change, atmospheric CO2 enhances plant growth by stimulating photosynthesis. In one scenario, adaptations to farming practices resulting from a lengthened growing season, elevated CO2- induced climate change, and enhanced plant growth were all factored into model simulations. The results predict that cotton yields would increase by as much as 26-36%.
"Cotton is a very important economic crop for U.S. agriculture," says NCAR's Linda Mearns, a co-author of the study. "This is the first time impacts of climate change on cotton production have been examined at this level of detail on a regional scale." Nevertheless, explains NCAR co-author Ruth Doherty, these cotton model projections are simplistic. For example, the climate models project climate change based on an instantaneous doubling of CO2, when in reality such increases would occur gradually over this century, possibly changing the outcomes. Still, in most of the scenarios there was a trend towards increased cotton yields in the future.
Two climate models were used in the study--a large-scale global climate model that used 300 by 300 kilometer (186 by 186 mile) grids, and a fine-scale regional climate model that used 50 by 50 kilometer (31 by 31 mile) grids. A climate model is a simplified mathematical representation of the earth's climate system, including data on the physical, geophysical, chemical, and biological processes that govern the climate system. Fine-scale models with higher resolution may be more accurate, but in order to gain information about the future regional climate, results from the global model must be used to initialize and control the regional model.
Using these two models, three scenarios were simulated. The first scenario simply looked at the impact that climate change resulting from an instantaneous doubling of CO2 would have on cotton yields in the southeastern United States, including Alabama, Arkansas, northern Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, and part of Tennessee. For this scenario the fine-scale model predicted a decrease of 10% in cotton yield over the region, while the large-scale model showed a 4% increase in yields.
When the climate change resulting from CO2 doubling was combined with the potential for enhanced cotton plant growth as a result of greater carbon availability, the fine-scale model showed a 5% increase in yields, while the large-scale model predicted a 16% increase. Finally, when the first two factors of CO2 doubling and enhanced growth were combined with farming adaptations, such as planting crops earlier to take advantage of a longer growing season, the fine-scale model predicted a 26% increase, and the large-scale model predicted a 36% increase.
The research is part of a larger project that examines the impact of different spatial scales of climate change scenarios on yields of corn, wheat, sorghum, soybeans, and cotton in the southeastern United States. The findings will be published next year in a special issue of the journal Climate Change. NASA and the U.S. Environmental Protection Agency funded the study. NCAR's primary sponsor is the National Science Foundation.
UCAR and NCAR news: http://www.ucar.edu/communications/newsreleases/2001.
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