Effects of multi-observations uncertainty and models similarity on climate change projections
KAUST DepartmentPhysical Science and Engineering (PSE) Division
Earth Science and Engineering Program
Extreme Computing Research Center
KAUST Grant NumberREP/1/3268-01-01
Permanent link to this recordhttp://hdl.handle.net/10754/690130
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AbstractClimate change projections (CCPs) are based on the multimodel means of individual climate model simulations that are assumed to be independent. However, model similarity leads to projections biased toward the largest set of similar models and intermodel uncertainty underestimation. We assessed the influences of similarities in CMIP6 through CMIP3 CCPs. We ascertained model similarity from shared physics/dynamics and initial conditions by comparing simulated spatial temperature and precipitation with the corresponding observed patterns and accounting for intermodel spread relative to the observational uncertainty, which is also critical. After accounting for similarity, the information from 57 CMIP6, 47 CMIP5, and 24 CMIP3 models can be explained by just 11 independent models without significant differences in globally averaged climate change statistics. On average, independent models indicate a lower global-mean temperature rise of 0.25 °C (~0.5 °C–1 °C in some regions) relative to all models by the end of the 21st century under CMIP6’s highest emission scenario.
CitationPathak, R., Dasari, H. P., Ashok, K., & Hoteit, I. (2023). Effects of multi-observations uncertainty and models similarity on climate change projections. Npj Climate and Atmospheric Science, 6(1). https://doi.org/10.1038/s41612-023-00473-5
SponsorsThe Program for Climate Model Diagnosis and Intercomparison is acknowledged for making CMIP model data publicly available. The supercomputing facility at King Abdullah University of Science and Technology (KAUST) is acknowledged for providing fast computation and analysis support. NCAR-NCL and MATLAB software were used for data processing and visualization. This research was supported by the Office of Sponsored Research at KAUST under the Virtual Red Sea Initiative (REP/1/3268-01-01), the Saudi ARAMCO Marine Environmental Research Center, and the Climate Change Center at KAUST.
PublisherSpringer Science and Business Media LLC
Except where otherwise noted, this item's license is described as Archived with thanks to npj Climate and Atmospheric Science under a Creative Commons license, details at: https://creativecommons.org/licenses/by/4.0