U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


How Well Do Global Gridded Crop Models (GGCMs) Replicate the Responsiveness of Historical US Yields to Weather?
Published: July 10, 2017
Posted: January 19, 2018

Econometric analyses uncover differences among crop simulations, and between models and observations, in the responsiveness of yields of US major crops to heat and moisture.

The Science
Understanding how yields of major calorie crops respond to weather shocks helps clarify the potential benefits and/or risks of future climate change. Empirical climate change economics studies derive yield responses to temperature and precipitation as simplified, reduced-form relationships using statistical models estimated on observed agricultural production, harvested area and weather. In crop simulations, yield changes are emergent behavior determined by complex interactions among multiple plant growth processes. Researchers at Boston University and Fondazione Eni Enrico Mattei (Italy), working within a multi-institutional Cooperative Agreement led by Stanford University, estimated econometric models of crop yields using observations and crop simulations for identical historical periods and US locations.  The researchers compared the resulting reduced-form responses, thereby demonstrating that GGCMs’ yields tended to be more sensitive to adverse weather (extreme high temperature and/or low precipitation) exposures.

The Impact
Different GGCMs simulate different crop yield changes when forced with the same pattern of historical change in climate. To have confidence in GGCMs’ projections of the future impacts of climate change, and to drive model development, it is important to assess their skill against observations, and understand why differences might arise. This paper develops a method for diagnosing differences in GGCMs’ responses, and for attributing these differences to model characteristics.

Summary
Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, the researchers provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. They examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (US) against US Department of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, the research team estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. Results demonstrate that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.

Contacts (BER PM)
Bob Vallario
Integrated Assessment Research
Bob.Vallario@science.doe.gov

(PI Contact)
John Weyant
Stanford University
weyant@stanford.edu

Funding
This work was supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research Program, Integrated Assessment Research Program, Grant no. DE-SC0005171.

Publications
Mistry, M., I. Sue Wing and E. De Cian. 2017. “Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change,” Environmental Research Letters 12:75007. DOI: 10.1088/1748-9326/aa788c

Related Links
Supplementary Material: PDF

Topic Areas:

  • Research Area: Multisector Dynamics (formerly Integrated Assessment)

Division: SC-23.2 Biological Systems Science Division, BER

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

Aug 24, 2019
New Approach for Studying How Microbes Influence Their Environment
A diverse group of scientists suggests a common framework and targeting of known microbial processes [more...]

Aug 08, 2019
Nutrient-Hungry Peatland Microbes Reduce Carbon Loss Under Warmer Conditions
Enzyme production in peatlands reduces carbon lost to respiration under future high temperatures. [more...]

Aug 05, 2019
Amazon Forest Response to CO2 Fertilization Dependent on Plant Phosphorus Acquisition
AmazonFACE Model Intercomparison. The Science Plant growth is dependent on the availabi [more...]

Jul 29, 2019
A Slippery Slope: Soil Carbon Destabilization
Carbon gain or loss depends on the balance between competing biological, chemical, and physical reac [more...]

Jul 15, 2019
Field Evaluation of Gas Analyzers for Measuring Ecosystem Fluxes
How gas analyzer type and correction method impact measured fluxes. The Science A side- [more...]

List all highlights (possible long download time)