How well have CMIP3, CMIP5 and CMIP6 future climate projections portrayed the recently observed warming

• Published in: Scientific reports Vol. 12; no. 1; p. 11983
• Main Authors: Carvalho, D., Rafael, S., Monteiro, A., Rodrigues, V., Lopes, M., Rocha, A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.07.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 704/106/35; 704/106/694; Climate change; Emissions; Global warming; Greenhouse effect; Greenhouse gases; Humanities and Social Sciences; Intergovernmental Panel on Climate Change; multidisciplinary; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-16264-6

Despite the dire conclusions of the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports in terms of global warming and its impacts on Earth’s climate, ecosystems and human society, a skepticism claiming that the projected global warming is alarmist or, at least, overestimated, still persists. Given the years passed since the future climate projections that served as basis for the IPCC 4th, 5th and 6th Assessment Reports were released, it is now possible to answer this fundamental question if the projected global warming has been over or underestimated. This study presents a comparison between CMIP3, CMIP5 and CMIP6 future temperature projections and observations. The results show that the global warming projected by all CMIPs and future climate scenarios here analyzed project a global warming slightly lower than the observed one. The observed warming is closer to the upper level of the projected ones, revealing that CMIPs future climate scenarios with higher GHG emissions appear to be the most realistic ones. These results show that CMIPs future warming projections have been slightly conservative up to 2020, which could suggest a similar cold bias in their warming projections up to the end of the current century. However, given the short future periods here analyzed, inferences about warming at longer timescales cannot be done with confidence, since the models internal variability can play a relevant role on timescales of 20 years and less.