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Forcing and feedback in the MPI-ESM-LR coupled model under abruptly quadrupled CO2

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Block,  K.
Climate Dynamics, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37260

Mauritsen,  T.
Climate Dynamics, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Block, K., & Mauritsen, T. (2013). Forcing and feedback in the MPI-ESM-LR coupled model under abruptly quadrupled CO2. Journal of Advances in Modeling Earth Systems, 5, 676-691. doi:10.1002/jame.20041.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0014-3189-5
Abstract
Radiative feedback mechanisms associated with temperature, water vapor, cloud, and surface albedo change determine climate sensitivity to radiative forcing. Here we use the linearized radiative kernel-technique in combination with a Gregory analysis to determine the strength and structure of feedbacks, as well as direct and adjusted CO2 forcings in the coupled Max Planck Institute Earth System Model at base resolution (MPI-ESM-LR). We show that the combined Kernel-Gregory approach yields an elegant separation of surface temperature-dependent feedbacks from contributions to radiative forcing by fast adjustments. MPI-ESM-LR exhibits a relatively large cloud adjustment of nearly 2 W m−2 in direct response to quadrupled CO2, with positive cloud adjustment evident throughout the tropics, subtropics and over most landmasses whereas midlatitude storm tracks contribute negatively. The model features a nonlinear regression of radiation imbalance to global mean surface temperature change, resulting in a significantly increasing effective climate sensitivity after about 20 years which is approximately at temperatures 4–5 K above preindustrial. This feature is not uncommon among climate models and is relevant for future climate projections. We analyze the contribution of the individual feedback processes to this behavior and discuss possible origins such as differential ocean warming patterns associated with deep-ocean heat uptake or state dependencies of the feedback processes.