Large-scale crop yield failures are increasingly associated with food price spikes and food insecurity and are a large source of income risk for farmers. While the evidence linking extreme weather to yield failures is clear, consensus on the broader set of weather drivers and conditions responsible for recent yield failures is lacking. We investigate this for the case of four major crops in Germany over the past 20 years using a combination of machine learning and process-based modelling. Our results confirm that years associated with widespread yield failures across crops were generally associated with severe drought, such as in 2018 and to a lesser extent 2003. However, for years with more localized yield failures and large differences in spatial patterns of yield failures between crops, no single driver or combination of drivers was identified. Relatively large residuals of unexplained variation likely indicate the importance of non-weather related factors, such as management...

中文翻译：

---

德国没有完美的农作物歉收风暴

大规模农作物减产与粮食价格上涨和粮食不安全问题日益相关，是农民收入风险的重要来源。尽管将极端天气与产量下降联系在一起的证据很明确，但仍缺乏关于造成近期产量下降的更广泛的天气驱动因素和条件的共识。我们结合机器学习和基于过程的建模方法，对过去20年中德国四种主要农作物的情况进行了调查。我们的结果证实，与整个农作物普遍的产量下降相关的年份通常与严重的干旱有关，例如在2018年和2003年的程度较小。但是，对于那些局部农作物产量下降且农作物之间的产量下降空间格局差异较大的年份，未标识单个驱动程序或驱动程序组合。