Preprints
https://doi.org/10.5194/egusphere-2025-2599
https://doi.org/10.5194/egusphere-2025-2599
26 Jun 2025
 | 26 Jun 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Introducing FRIDA v2.1: A feedback-based, fully coupled, global integrated assessment model of climate and humans

William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen

Abstract. The current crop of models assessed by the Intergovernmental Panel on Climate Change (IPCC) to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities. These changes in human activities are critical to understanding the co-evolution of the climate and human systems. Earth System Models (ESMs) that represent the climate system and Integrated Assessment Models (IAMs) that represent the human system are typically separate, with assumptions coordinated through RCPs and SSPs in ScenarioMIP, the core scenario analysis protocol. This divide limits understanding of climate-human feedback. An alternative approach, such as the one used to build the Feedback-based knowledge Repository for IntegrateD Assessments "FRIDA" v2.1 IAM documented here, integrates climate and human systems into a unified global model, prioritizing feedback dynamics while maintaining interpretability. It represents the Earth's radiation balance, carbon cycle, and relevant portions of the water cycle alongside human demographics, economics, agriculture, and human energy use. Built using the System Dynamics method, it contains seven interconnected modules. Each subsystem is calibrated to data and validated to ensure structurally appropriate behaviour representation. FRIDA demonstrates that an aggregate, feedback-driven modelling approach, capturing climate-human interconnections with rigorous measurements of uncertainty, is possible. It complements conventional IAMs by highlighting missing feedback structures that affect future projections. Our work with FRIDA suggests SSP1-Baseline, SSP2-Baseline, and SSP5-Baseline are all overly optimistic on the prospects for future economic growth due to these feedbacks, while SSP3-Baseline and SSP4-Baseline, the SSPs with the highest challenges to adaptation, align more closely with our results. Future work will further refine climate impact representations, energy modelling, policy scenario creation, and stakeholder engagement for informed policymaking.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen

Status: open (until 21 Aug 2025)

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William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen

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Short summary
The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA v2.1 integrates these systems and generate results that suggest standard scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
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