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Updated: Sep 7, 2026

Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
Published on: December 12, 2013
ENSO redistributes hot-dry-windy exposure hours to reorganize winter wheat tail risk
Oumeng Qiao1, Honglei Che2, Buchun Liu3
1Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, 100081, China; State Key Laboratory of Efficient Utilization of Agricultural Water Resources, CAU/CAAS, Beijing, 100081, China; Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China; Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing, 100081, China; Key Laboratory of Modern Agricultural Equipment, Ministry of Agriculture and Rural Affairs,PR China, Nanjing, 210014, China.
Abstract:
Large-scale climate modes such as ENSO influence crop production, yet the pathways linking remote variability to local losses remain unclear. Here, we link the El Niño-Southern Oscillation to winter wheat risk across China using heading-harvest hot-dry-windy hours from hourly ERA5-Land and 1981-2020 county-level yields. ENSO does not shift exposure uniformly; it redistributes probability mass along the HDW-hour distribution in a region-dependent way, changing the likelihood of high-exposure seasons. This imprint widens and left-shifts the yield-anomaly distribution and thickens the negative tail, consistent with thresholded, convex damage under late-season compound stress. Mediation decomposition indicates spatial asymmetry: HDW-mediated effects are clearest in southern latitude bands, whereas northern ENSO-yield variation is more strongly associated with competing non-HDW pathways. A targeted northern diagnosis identifies late frost as the strongest adverse non-HDW pathway, counterbalanced by a spring-precipitation pathway of comparable magnitude but opposite sign. A structural equation model supports a layered cascade in which ENSO intensifies extreme heat, the dominant proximal driver of HDW exposure, while irrigation intensity and soil organic carbon primarily damp exposure-to-loss translation.
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