Abstract. Unfavourable weather is a common cause for crop failures all over the world. Whilst extreme weather conditions may cause extreme impacts, crop failure commonly is induced by the occurrence of multiple and combined anomalous meteorological drivers. For these cases, the explanation of conditions leading to crop failure is complex, as the links connecting weather and crop yield can be multiple and non-linear. Furthermore, climate change is likely to perturb the meteorological conditions, possibly altering the occurrences of crop failures or leading to unprecedented drivers of extreme impacts. The goal of this study is to identify important meteorological drivers that cause crop failures and to explore changes in crop failures due to global warming. For that, we focus on a historical failure event, the extreme low soybean production during the 2012 season in the midwestern US. We first train a random forest model to identify the most relevant meteorological drivers of historical crop failures and to predict crop failure probabilities. Second, we explore the influence of global warming on crop failures and on the structure of compound drivers. We use large ensembles from the EC-Earth global climate model, corresponding to present-day, pre-industrial +2 and 3 ∘C warming, respectively, to isolate the global warming component. Finally, we explore the meteorological conditions inductive for the 2012 crop failure and construct analogues of these failure conditions in future climate settings. We find that crop failures in the midwestern US are linked to low precipitation levels, and high temperature and diurnal temperature range (DTR) levels during July and August. Results suggest soybean failures are likely to increase with climate change. With more frequent warm years due to global warming, the joint hot–dry conditions leading to crop failures become mostly dependent on precipitation levels, reducing the importance of the relative compound contribution. While event analogues of the 2012 season are rare and not expected to increase, impact analogues show a significant increase in occurrence frequency under global warming, but for different combinations of the meteorological drivers than experienced in 2012. This has implications for assessment of the drivers of extreme impact events.
Globally soybeans form the main source of protein for livestock feed, the second most consumed type of vegetable oil, and are commonly consumed by humans (Hartman et al., 2011). In spite of its global importance, 80% of the soybean production is concentrated in hotspot regions in the United States of America (US), Brazil, and Argentina (FAO, 2022). Simultaneous disruptions in these regions have thus considerable impacts on the global supply chain of soybeans, as was observed in the year of 2012. In that year, low soybean yields in all three countries simultaneously led to soybean shortages and high prices on global markets (FAO, 2022;Zhang et al., 2018). Climate change affects the occurrence and characteristics of extreme events in agriculture (IPCC, 2022). Understanding how climate change affects large-scale events such as the 2012 offers relevant insights into the risks and challenges that the globalized agricultural system might face in the future.
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