Democratizing climate modeling for more pertinent and accurate policy insights — Interview with Prof. Roberto Schaeffer.
Integrated Assessment Models (IAMs) play a pivotal role in shaping climate research and policy. “The main progress lies in democratizing modeling capabilities across different countries, ensuring more pertinent and accurate policy insights,” says Roberto Schaeffer. The need for a shift towards national-level modeling of climate impacts, the complexity of balancing immediate costs with long-term benefits at the policy level, and the representation gap between countries, are at the core of the current discussion around climate modeling.
In an interview with Roberto Schaeffer, full professor of Energy Economics at the Programa de Planejamento Energético (PPE/COPPE/UFRJ), we uncover the intricacies of integrating climate change models into policy decisions, navigating the fine line between immediate costs and long-term benefits. While addressing the challenges and the potentialities of IAMs, Schaeffer acknowledges the inevitability of the search for a sustainable future.
What is the role of IAMs in climate research and policy?
Most of my work revolves around models, and I think models are becoming more and more important. As of today, global models dominate the scene, and over the past two decades Europe has been a hub for their development. Significant capabilities exist for example at IIASA in Austria, PBL in the Netherlands, PIK in Germany, CMCC in Italy, with some capabilities in China and India.
Fortunately, my group in Brazil has substantial capabilities, making it “ the new kid on the block” in this field. However, these global models present a challenge- they lack the resolution to reach the country level. While they may divide the world into regions, such as the U.S.A., Japan, China, India, Brazil, and Europe, the resolution remains insufficient.
In order to make these models really useful, we aim to develop capabilities in many countries, encouraging the creation of models tailored to represent their unique realities. This movement towards national-level modeling is gaining traction, fostering a more democratic approach where each country develops its own model for better representation. Recognizing the limitations of global models at the national level, this shift allows for more reliable and policy-relevant results specific to individual countries. The main progress lies in democratizing modeling capabilities across different countries, ensuring more pertinent and accurate policy insights.
Why is it necessary to build models with country-level resolution?
The impacts of climate change don’t affect everyone equally. As a middle-class person from Brazil, I might not be directly impacted, and if it gets warmer I can handle it. On the other hand, poor people in poorer countries will be disproportionately affected. This is why getting a global agreement on solving the problem is not easy. During my long experience with the IPCC, I bore witness to the struggle to approve reports, given the diverse positions of countries like India, China, Brazil, and Mexico compared to other countries in northern Europe or North America for example.
Aligning countries with such different geographical and social realities makes global agreements challenging. The current top-down approach doesn’t necessarily address the regional and income-level variations in impact. Deciding on temperature targets is complicated because what might be acceptable for a country like Canada could be detrimental for small islands like Tuvalu. Technically speaking, we know how to solve this problem but politically it’s not that easy.
What challenges arise in integrating climate change models into policy-making decisions?
It is a long process because decisions made today, inducing immediate costs for policymakers, will only yield major benefits in five or ten years. The collaboration between modelers and policymakers is crucial, and it is already happening. Yet, a substantial gap in understanding persists, particularly in practical aspects and associated costs. The challenge lies in prioritizing present concerns over future ones, as human behavior tends to value immediate gains, making it challenging to garner support for initiatives that primarily benefit future generations. Human beings are very complicated.
There is another crucial problem here. Even with the most rigorous scientific models, uncertainties persist. Computational challenges lead us to run models deterministically, presenting results with an associated uncertainty level. However, when communicating this uncertainty to policymakers or the general population, it is often perceived as a lack of precision or knowledge. This creates complexity, as decisions need to be made today based on technically sound information. Politicians, concerned with immediate mandates, may find it uncomfortable to bear the burden of decisions that impact the future, a challenge exacerbated by the perceived temporal distance of climate change impacts. I think the difficulty of the problem is exactly there — people in power thinking “the future is not my problem”.
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Climate Foresight is published by the CMCC Foundation , a research center that develops models and predictions to study the interaction between changes in the climate system and social, economic and environmental changes. Climate Foresight is an observatory on tomorrow, a digital magazine that collects ideas, interviews, articles, art performances, and multimedia to tell the stories of the future.
