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更大规模的海洋-大气模式驱动了小麦产量的协同变化和全球波动。

Larger-scale ocean-atmospheric patterns drive synergistic variability and world-wide volatility of wheat yields.

机构信息

Civil Engineering Department, The City College of New York, The City University of New York, New York City, 10031, USA.

Advanced Science Research Center, The Graduate Center, The City University of New York, New York City, 10031, USA.

出版信息

Sci Rep. 2020 Mar 23;10(1):5193. doi: 10.1038/s41598-020-60848-z.

DOI:10.1038/s41598-020-60848-z
PMID:32251341
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7090071/
Abstract

Diagnosing potential predictability of global crop yields in the near term is of utmost importance for ensuring food supply and preventing socio-economic consequences. Previous studies suggest that a substantial proportion of global wheat yield variability depends on local climate and larger-scale ocean-atmospheric patterns. The science is however at its infancy to address whether synergistic variability and volatility (major departure from the normal) of multi-national crop yields can be potentially predicted by larger-scale climate drivers. Here, using observed data on wheat yields for 85 producing countries and climate variability from 1961-2013, we diagnose that wheat yields vary synergistically across key producing nations and can also be concurrently volatile, as a function of shared larger-scale climate drivers. We use a statistical approach called robust Principal Component Analysis (rPCA), to decouple and quantify the leading modes (PC) of global wheat yield variability where the top four PCs explain nearly 33% of the total variance. Diagnostics of PC1 indicate previous year's local Air Temperature variability being the primary influence and the tropical Pacific Ocean being the most dominating larger-scale climate stimulus. Results also demonstrate that world-wide yield volatility has become more common in the current most decades, associating with warmer northern Pacific and Atlantic oceans, leading mostly to global supply shortages. As the world warms and extreme weather events become more common, this diagnostic analysis provides convincing evidence that concurrent variability and world-wide volatility of wheat yields can potentially be predicted, which has major socio-economic and commercial importance at the global scale, underscoring the urgency of common options in managing climate risk.

摘要

诊断近期全球作物产量的潜在可预测性对于确保粮食供应和防止社会经济后果至关重要。先前的研究表明,全球小麦产量变化的很大一部分取决于当地气候和更大规模的海洋-大气模式。然而,科学界还处于起步阶段,无法确定多国作物产量的协同变化和波动性(与正常情况的重大偏离)是否可以通过更大规模的气候驱动因素来预测。在这里,我们使用 1961-2013 年期间 85 个生产国的小麦产量观测数据和气候可变性,诊断出关键生产国的小麦产量存在协同变化,并且由于共享更大规模的气候驱动因素,也可能同时具有波动性。我们使用一种称为稳健主成分分析(rPCA)的统计方法,将全球小麦产量变化的主要模式(PC)解耦并量化,其中前四个 PC 解释了近 33%的总方差。PC1 的诊断表明,前一年的当地空气温度变化是主要影响因素,热带太平洋是最主要的更大规模气候刺激因素。结果还表明,在当前的几十年中,世界范围内的产量波动性变得更加普遍,与更温暖的北太平洋和北大西洋有关,主要导致全球供应短缺。随着全球变暖,极端天气事件变得更加普遍,这种诊断分析提供了令人信服的证据,表明小麦产量的协同变化和全球波动性可能是可以预测的,这在全球范围内具有重大的社会经济和商业重要性,强调了在管理气候风险方面采取共同选择的紧迫性。

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