The HadGEM3‐GC3.1 Contribution to the CMIP6 Detection and Attribution Model Intercomparison Project

• Published in: Journal of Advances in Modeling Earth Systems
• Main Authors: Gareth S. Jones, Martin B. Andrews, Timothy Andrews, Ed Blockley, Andrew Ciavarella, Nikos Christidis, Daniel F. Cotterill, Fraser C. Lott, Jeff Ridley, Peter A. Stott
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2024
• Subjects: climate models; CMIP6; DAMIP; detection and attribution; Physical geography; GB3-5030; Oceanography; GC1-1581; Southern Ocean
• Online Access: https://doi.org/10.1029/2023MS004135; https://doaj.org/article/f20eb48f3bd145f5b0cb748653deff6d

Abstract The UK contribution to the Detection and Attribution Model Intercomparison Project (DAMIP), part of the sixth phase of the Climate Model Intercomparison Project (CMIP6), is described. The lower atmosphere and ocean resolution configuration of the latest Hadley Centre global environmental model, HadGEM3‐GC3.1, is used to create simulations driven either with historical changes in anthropogenic well‐mixed greenhouse gases, anthropogenic aerosols, or natural climate factors. Global mean near‐surface air temperatures from the HadGEM3‐GC31‐LL simulations are consistent with CMIP6 model ensembles for the equivalent experiments. While the HadGEM3‐GC31‐LL simulations with anthropogenic and natural forcing factors capture the overall observed warming, the lack of marked simulated warming until the 1990s is diagnosed as due to aerosol cooling mostly offsetting the well‐mixed greenhouse gas warming until then. The model has unusual temperature variability over the Southern Ocean related to occasional deep convection bringing heat to the surface. This is most prominent in the model's aerosol only simulations, which have the curious feature of warming in the high southern latitudes, while the rest of the globe cools, a behavior not seen in other CMIP6 models. This has implications for studies that assume model responses, from different climate drivers, can be linearly combined. While DAMIP was predominantly designed for detection and attribution studies, the experiments are also very valuable for understanding how different climate drivers influence a model, and thus for interpretating the responses of combined anthropogenic and natural driven simulations. We recommend institutions provide model simulations for the high priority DAMIP experiments.