Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates

• Main Authors: Modak, Angshuman, Mauritsen, Thorsten
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2022
• Subjects: article; Verlagsveröffentlichung; Sea ice
• Online Access: https://doi.org/10.5194/egusphere-2022-976; https://noa.gwlb.de/receive/cop_mods_00062838; https://egusphere.copernicus.org/preprints/egusphere-2022-976/egusphere-2022-976.pdf

Equilibrium climate sensitivity (ECS) constrained based on the instrumental record of the historical warming becomes coherent with other lines evidence when the dependence of radiative feedbacks on the pattern of surface temperature change (pattern effect) is incorporated. Pattern effect strength is usually estimated with atmosphere-only model simulations forced with observed historical sea-surface temperature (SST) and sea-ice change, and constant pre-industrial forcing. However, recent studies indicate that pattern effect estimates depend on the choice of SST boundary condition dataset, due to differences in the measurement sources and the techniques used to merge and construct them. Here, we systematically explore this dataset dependency by applying seven different observed SST datasets to the MPI-ESM1.2-LR model covering 1871–2017. We find that the pattern effect ranges from -0.01 ± 0.09 Wm-2 K-1 to 0.42 ± 0.10 Wm-2 K-1 (standard error), whereby the commonly used AMIPII dataset produces by far the largest estimate. When accounting for the generally weaker pattern effect in MPI-ESM1.2-LR compared to other models, as well as dataset dependency and inter-model spread, we obtain a combined pattern effect estimate of 0.30 Wm-2 K-1 [-0.14 to 0.74 Wm-2 K-1] (5–95 percentiles) and a resulting instrumental record ECS estimate of 3.1 K [1.7 to 9.2 K], which is slightly lower and better constrained than in previous studies.