The authors of the paper used a statistical approach pairing past climate data in Brazil with information on crop productivity, farm revenue and agricultural loan performance. They combined this data with climate simulations to predict future weather conditions and their impacts on farming and how those changes will affect financial institutions.
“A difficulty in studying climate impacts on agriculture is that there are all sorts of adaptations happening all the time that aren’t easily observed, but are really important for understanding vulnerability and how risk is changing,” said coauthor Jennifer Burney, professor of environmental science at UC San Diego’s School of Global Policy and Strategy and Scripps Institution of Oceanography. “We were able to distinguish signals from different types of climate impacts and which ones led to this larger financial risk.”
Systematic thinking about building resilience against climate change around the globe
A key objective of the research is to support resilient food security under a changing climate, which requires understanding of when small climate shifts might have outsized impacts, spilling across regions or into other sectors through institutions like trade and banking.
Understanding the systemic risk posed by climate change is especially helpful for policymakers and disaster relief agencies, as climate change has increasingly become a national security threat. To that end, the statistical approach developed in the study could be applied around the globe.
“The technique we developed will help populations identify where they are most vulnerable, how climate change will hurt them the most economically and what institutions they should focus on to build resilience,” said study coauthor Craig McIntosh, professor of economics at the School of Global Policy and Strategy.
For example, some governments in the Western Pacific region buy extra food on the global market in emerging El Niño years, when their own crop productivity suffers. The statistical approach used in the study could help governments around the world understand their own climate conditions and whether local, regional or international institutions will be best placed to address them.
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