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Abstract Comprehensive climate model simulations with perturbed sea ice covers have been extensively used to assess the impact of future sea ice loss, suggesting substantial climate changes both in the high latitudes and beyond. However, previous work using an idealized energy balance model calls into question the methods that are used to perturb sea ice cover, demonstrating a consistent overestimate of the surface warming due to sea ice loss, while the large complexity gap between the idealized and comprehensive models makes the implications of this result unclear. To bridge this gap we have performed simulations with a new implementation of the CESM2 model in a slab ocean aquaplanet configuration coupled with thermodynamic sea ice, which is able to capture the realistic seasonal characteristics of polar climate change. Using this model setup, we perform a suite of experiments to systematically quantify the spurious climate responses associated with melting sea ice without a CO₂forcing. We find that using the sea ice ghost flux method overestimates many aspects of the climate response by 10%–20%, including the polar warming, the mini global warming signal and the increase in both precipitation and evaporation. The location of the latitudinal band of heating applied to melt the sea ice relative to the midlatitude jet is important for determining where the midlatitude circulation response is overestimated. This work advances our ability to isolate the true climate response to sea ice loss, and provides a framework for conducting coupled sea ice loss simulations absent the spurious impacts from the addition of artificial heating. 

Previous work identified an anthropogenic fingerprint pattern in 𝑇AC (𝑥, 𝑡), the amplitude of the seasonal cycle of mid- to upper tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite 𝑇AC(𝑥,𝑡) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their 𝑇AC (𝑥, 𝑡) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3-4) inter-model and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal 𝑇AC(𝑥,𝑡) variability associated with the Atlantic Multidecadal Oscillation and the El Niño~Southern Oscillation. The robustness of the seasonal cycle D&A results shown here, taken together with the evidence fromidealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced𝑇AC(𝑥,𝑡) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.