TY - JOUR
T1 - Comparison of agricultural impacts of climate change calculated from high and low resolution climate change scenarios
T2 - Part I. The uncertainty due to spatial scale
AU - Mearns, L. O.
AU - Easterling, W.
AU - Hays, C.
AU - Marx, D.
N1 - Funding Information:
Fifty percent of this research was funded by the U.S. Department of Energy’s (DOE) National Institute for Global Environmental Change (NIGEC) through the NIGEC Great Plains Regional Center at the University of Nebraska–Lincoln. (DOE Cooperative Agreement No. DE-FC03-90ER61010.) Financial support does not constitute an endorsement by DOE of the views expressed in this article. We thank John Katzfey, John McCregor, and Ian Watterson of the Commonwealth Scientific and Industrial Organization of Australia (CSIRO) for providing the output from the CSIRO climate model runs. We thank Dr. Timothy Haas of the University of Wisconsin, Milwaukee for advice on the use of spatial statistics. We also thank Elena Tvetsinskaya of NCAR for making some statistical calculations and Larry McDaniel of NCAR for assistance with graphics. Finally, we thank the three anonymous reviewers and two secondary reviewers for their valuable comments and suggestions.
Funding Information:
★ The National Center for Atmospheric Research is sponsored by the National Science Foundation.
PY - 2001
Y1 - 2001
N2 - We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects of CO2 fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 × CO2 runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate change scenarios as an important uncertainty for climate change impacts analysis.
AB - We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects of CO2 fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 × CO2 runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate change scenarios as an important uncertainty for climate change impacts analysis.
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U2 - 10.1023/A:1012297314857
DO - 10.1023/A:1012297314857
M3 - Article
AN - SCOPUS:0034760369
SN - 0165-0009
VL - 51
SP - 131
EP - 172
JO - Climatic Change
JF - Climatic Change
IS - 2
ER -