Climate anomalies pose risks to agriculture and food security. To assess the impact, this paper models the complex dependences of climate extreme indices and the crop-related variables: yield, production, and price of a crop. Using a comprehensive copula-based analysis, the conditional distributions of the crop-related variables given extremes of air temperature and precipitation are estimated. We used potatoes in the Netherlands as a case study. Weather data were obtained from 33 weather stations and ECMWF ERA-interim archive during the period 1980–2017. A joint behavior analysis predicted the yield, the production and the price with the relative mean absolute error equal to 5.4%, 3.6%, and 27.9%, respectively. The study showed that copulas adequately describe the multivariate dependences. Those in turn are able to quantify the impact of climate extremes, including their uncertainties.

气候异常对农业和粮食安全构成威胁。为了评估影响，本文对气候极端指数和与作物相关的变量（作物的产量，产量和价格）的复杂依赖性进行了建模。使用全面的基于copula的分析，在极端气温和降水的情况下，估算了与作物有关的变量的条件分布。我们以荷兰的马铃薯为案例研究。在1980年至2017年期间，从33个气象站和ECMWF ERA临时存档中获取了气象数据。联合行为分析预测了产量，产量和价格，相对平均绝对误差分别等于5.4％，3.6％和27.9％。研究表明，copulas充分描述了多元依赖性。