Abstract
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.
| Original language | English |
|---|---|
| Article number | 100227 |
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Weather and climate extremes |
| Volume | 26 |
| Early online date | 18 Sept 2019 |
| DOIs | |
| Publication status | Published - Dec 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
Keywords
- ITC-ISI-JOURNAL-ARTICLE
- ITC-GOLD
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