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Substantial contribution of internal variability to satellite-era tropospheric warming inferred from CMIP6 large ensembles

Presentation Date
Friday, December 16, 2022 at 5:00pm - Friday, December 16, 2022 at 5:12pm
McCormick Place - E253ab



Observations of surface and tropospheric temperature change since the late-1970s exhibit less warming than the average warming in coupled climate model simulations, particularly in the tropical troposphere. One possible explanation for the difference in the rate of model-versus-observed warming is that the average model sensitivity to greenhouse gas forcing is too large. Another possibility is that satellite observations underestimate tropospheric warming. Recent work has also demonstrated that deficiencies in the aerosol forcing enhance model warming and that natural internal climate variability has reduced satellite-era warming in the observed record. Each of these factors needs to be assessed to determine their contribution to model-versus-observed differences in the rate of tropical and global mean warming.

In this analysis, we seek to quantify the contribution of internal variability to satellite-era (1979 – 2014) tropical tropospheric warming. We apply a range of techniques, including linear regression and neural network analysis, to large model initial condition ensembles to quantify and separate the forced and unforced component of tropospheric warming. We find that these techniques are skillful in separating and quantifying the forced and unforced components of tropical tropospheric warming. In applying this methodology to observations, our results indicate that internal variability has substantially reduced warming over the satellite era, particularly in the tropics. These results indicate that internal variability must be accounted for when evaluating climate models and when inferring transient and equilibrium climate sensitivity from the observed record.

Funding Program Area(s)