Robust climate change research: A review on multi-model analysis

Significant differences in key results across the various climate models and integrated assessment models (IAMs) represent a critical challenge to reliable scientific findings and the robust design of climate policies, which leads to an enormous amount of attention and the urgent call for a multi-model study. In this paper, we develop an integrated literature-survey framework by combining the typical content analysis with a simple statistical analysis to systematically examine the developing trends of IAM-based multi-model studies and explore the model-robust climate policy findings; we also conduct an extended analysis to identify the role of a multi-model approach in global warming and other global change research by employing co-citation network analysis. The results reveal that multi-model comparison and ensemble are effective methods to explore reliable scientific findings and yield robust policy conclusions. The current multi-model studies are sparse as a whole, especially for IAM-based climate economic and policy research; future multi-model works, at both the global and regional levels, are therefore promising. We observe that the developed countries (the EU and the US) dominate the current multi-model study, which could be proved by the number of primary IAMs developed, frequency of models adopted, and number of works published. Addressing the risks of global warming relies on reliable scientific research and robust climate policy design, particularly for the developing large emitters, which heavily depends on consistent efforts toward primary model development and comprehensive cooperation with state-of-the-art model teams all over the world.