The Role of Climate Covariability on Crop Yields in the Conterminous United States
Abstract
The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R, an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop modelmore »
- Authors:
-
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Joint Global Change Research Inst.
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Atmospheric Sciences & Global Change Division
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Laboratory Directed Research and Development (LDRD) Program; National Aeronautics and Space Administration (NASA)
- OSTI Identifier:
- 1357048
- Report Number(s):
- PNNL-SA-116570
Journal ID: ISSN 2045-2322; PII: BFsrep33160
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Scientific Reports
- Additional Journal Information:
- Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 2045-2322
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Leng, Guoyong, Zhang, Xuesong, Huang, Maoyi, Asrar, Ghassem R., and Leung, L. Ruby. The Role of Climate Covariability on Crop Yields in the Conterminous United States. United States: N. p., 2016.
Web. doi:10.1038/srep33160.
Leng, Guoyong, Zhang, Xuesong, Huang, Maoyi, Asrar, Ghassem R., & Leung, L. Ruby. The Role of Climate Covariability on Crop Yields in the Conterminous United States. United States. https://doi.org/10.1038/srep33160
Leng, Guoyong, Zhang, Xuesong, Huang, Maoyi, Asrar, Ghassem R., and Leung, L. Ruby. Mon .
"The Role of Climate Covariability on Crop Yields in the Conterminous United States". United States. https://doi.org/10.1038/srep33160. https://www.osti.gov/servlets/purl/1357048.
@article{osti_1357048,
title = {The Role of Climate Covariability on Crop Yields in the Conterminous United States},
author = {Leng, Guoyong and Zhang, Xuesong and Huang, Maoyi and Asrar, Ghassem R. and Leung, L. Ruby},
abstractNote = {The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R, an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations.},
doi = {10.1038/srep33160},
journal = {Scientific Reports},
number = 1,
volume = 6,
place = {United States},
year = {Mon Sep 12 00:00:00 EDT 2016},
month = {Mon Sep 12 00:00:00 EDT 2016}
}
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