PNNL

Abstract

The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in 26 understanding the climate influence on crop yields. Here, we analyze county-level corn and 27 soybean yields and observed climate for the period 1983-2012 to understand how growing-28 season (June, July and August) mean T, P and R influence crop yields jointly and in isolation 29 across the CONterminous United States (CONUS). Results show that nationally averaged corn 30 and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% 31 can be significantly explained by T and P, respectively. By including R, an additional of 5% in 32 variability can be explained for both crops. Using partial regression analyses, we find that studies 33 that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of 34 crop yields to a single climate factor at the county scale. Further analyses indicate large spatial 35 variation in the relative contributions of different climate variables to the variability of historical 36 corn and soybean yields. The structure of the dominant climate factors did not change 37 substantially over 1983-2012, confirming the robustness of the findings, which have important 38 implications for crop yield prediction and crop model validations.