Abstract
Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms and the drivers of the projection uncertainties can help to improve decisions. Previous studies have provided important insights, but often sample only a small subset of potentially important uncertainties. Here we expand on a previous statistical modeling approach by refining the analyses of two uncertainty sources. Specifically, we assess the effects of uncertainties surrounding crop-yield model parameters and climate forcings on projected crop yield. We focus on maize yield projections in the eastern U.S.in this century. We quantify how considering more uncertainties expands the lower tail of yield projections. We characterized the relative importance of each uncertainty source and show that the uncertainty surrounding yield model parameters is the main driver of yield projection uncertainty.
Publication types
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, Non-P.H.S.
MeSH terms
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Crop Production
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Models, Statistical
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Uncertainty
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United States
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Zea mays / growth & development*
Grants and funding
HY, RN, SR and KK received support from the US Department of Energy, Office of Science through the Program on Coupled Human and Earth Systems (PCHES) under DOE Cooperative Agreement No. DE-SC0016162 (
https://www.energy.gov). HY, RN and KK received support from the National Science Foundation (NSF) through the Network for Sustainable Climate Risk Management (SCRiM) under NSF cooperative agreement GEO-1240507 (
https://www.nsf.gov). HY, RN, SR and KK also received support from Penn State (
https://www.psu.edu) through the Center for Climate Risk Management. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.