How Will Sea Level Rise Affect the Global Economy?
Globally, sea level rose by more than 0.5 cm in 2024, and the rate at which it is rising has been increasing. Accumulated over time, this will expose coastal regions around the world to increased risks of erosion and severe storm surges. Researchers generally rely on integrated assessment models to investigate how such changes affect societies. These models provide estimates of the economic costs of global climate change. However, although sea level rise plays an important role in this by creating significant socioeconomic pressure, it has only been considered in a highly simplified manner. Researchers from the Max Planck Institute for Meteorology (MPI-M) and their partners have created a new process-based model to better represent the impacts of sea level rise and the mechanisms humans may adopt to adapt.
Relevant socioeconomic feedbacks
The FRISIA model, named after the North Sea region, calculates the global impacts of sea level rise as a dynamic system that changes over time.
“Most previous models first calculate the total costs of sea level rise over a certain period of time for a variety of adaptation strategies and then select the optimal strategy. However, this approach is computationally expensive, and reality shows that social development often does not follow an optimal path that minimizes costs,” says Lennart Ramme, researcher at MPI-M and lead author of the study. “Therefore, we decided against optimization and prescribed different scenarios such as constructing sea walls or planned retreat from the coast. This allows for better temporal resolution, dynamic adaptation strategies, and the consideration of socioeconomic feedback.”
One example of an emerging feedback loop arises in coastal zones where adaptation via protection is limited by money availability and therefore becomes insufficient. In the long term, economic growth in these regions may decrease due to storm damages and reduced investment. As a consequence, even less money is available for the construction of protective structures, meaning that further storm surges can cause greater damage to the remaining assets. However, the total damages are reduced, because overall there are less assets located in the affected coastal zone.
More realistic impact assessment
By including these new feedbacks, FRISIA allows for a more realistic representation of different adaptation strategies. When coupled with the integrated assessment model FRIDA, the global consequences of sea level rise of approximately 0.8 meters by 2100 (corresponding to roughly a one percent yearly increase in the rate it is presently rising) can be evaluated. In such a scenario, global gross domestic product would decrease by 1.5 to 6.2 percent without adaptation measures, consistent with other models. With an adaptation strategy, the loss is limited to 0.5 to 3.2 percent.
“Thanks to the consideration of feedbacks, we were able to show that the damages caused by global sea level rise could peak in the first half of the 22nd century,” says co-author and MPI-M group leader Chao Li. “After that, they will decline because vulnerable assets will lose value and investments will tend to take place outside the areas at risk.”
Simpler models had not taken this into account.
Like the FRIDA integrated assessment model, the FRISIA model code is freely available and is under continuing development. FRISIA can also be linked to other integrated assessment models and promises more realistic insights into the socioeconomic impacts of sea level rise. Currently, the research team is investigating how delays and interruptions in the construction of protective structures affect the optimal adaptation strategy.
Original publication
Ramme, L., Blanz, B., Wells, C., Wong, T. E., Schoenberg, W., Smith, C., and Li, C. (2025) Feedback-based sea level rise impact modelling for integrated assessment models with FRISIAv1.0, Geosci. Model Dev., 18, 10017–10052. DOI: 10.5194/gmd-18-10017-2025
Contact
Dr. Lennart Ramme
Max Planck Institute for Meteorology
lennart.ramme@mpimet.mpg.de
Dr. Chao Li
Max Planck Institute for Meteorology
chao.li@mpimet.mpg.de