Climate and climate change in a radiative‐convective equilibrium version of ECHAM6

By Dagmar Popke, Bjorn Stevens, Aiko Voigt. 2013

190 citations recorded by the source corpus.

A radiative‐convective equilibrium (RCE) configuration of a comprehensive atmospheric general circulation model, ECHAM6, is coupled to a mixed‐layer ocean for the purpose of advancing understanding of climate and climate change. This configuration differs from a standard configuration only through the removal of land‐surface processes, spatial gradients in solar insolation, and the effects of rotation. Nonetheless, the model produces a climate that resembles the tropical climate in a control simulation of Earth's atmosphere. In the RCE configuration, regional inhomogeneities in surface temperature develop. These inhomogeneities are transient in time but sufficiently long‐lived to establish large‐scale overturning circulations with a distribution similar to the preindustrial tropics in the standard configuration. The vertical structure of the atmosphere, including profiles of clouds and condensate conditioned on the strength of overturning, also resembles those produced by a control simulation of Earth's tropical atmosphere. The equilibrium climate sensitivity of the RCE atmosphere can explain 50% of the global climate sensitivity of a realistic configuration of ECHAM6. Part of the difference is attributed to the lack of polar amplification in RCE. The remainder appears to be related to a less positive cloud shortwave feedback, which results from an increase in low cloudiness with increasing surface temperatures in the RCE configuration. The RCE configuration shows an increase of climate sensitivity in a warmer climate. The increase in climate sensitivity scales with the degree to which the upper‐troposphere temperature departs from a moist adiabat.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/c890cb09110ad36916ebc30601c485ca9edb9e62

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Citations in the corpus

Organization of tropical convection in low vertical wind shears: Role of updraft entrainment (2017, methodology): “Organization in global model simulations of RCE will thus also be sensitive to the convective parameterization scheme’s entrainment formulation [e.g. Popke et al., 2013; Reed et al., 2015; Coppin and Bony , 2015].”
Global‐scale convective aggregation: Implications for the Madden‐Julian Oscillation (2015, background): “So far, these studies have focused on questions of climate sensitivity and model development, but the configuration appears a promising tool for a wide range of applications [Held et al., 2007; Popke et al., 2013; Reed et al., 2015].”
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. (2016, methodology): “Additional experiments further idealizing the aquaplanet framework to a non-rotating rotationally symmetric case are also under development (e.g. Popke et al., 2013).”
Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2 (2019, methodology): “1 were required because of inconsistent formulations in the convection scheme, in the grid-scale stratiform cloud condensation scheme, and in the turbulence transfer scheme, causing violations of the atmospheric energy budget (Stevens et al., 2013).”
Could Machine Learning Break the Convection Parameterization Deadlock? (2018, background): “Entrainment is one of the major factors Confidential manuscript submitted to Geophysical Research Letters controlling climate sensitivity and explains, to a large extent, the intermodel spread in climate sensitivity in the tropics [ Popke et al. , 2013; Tomassini et al. , 2014].”
Self‐aggregation of convection in long channel geometry (2014, unknown): “…and Romps, 2013; Wing and Emanuel, 2014) to elongated channel 3D (Posselt et al., 2008, 2012; Stephens et al., 2008), as well as regional or global models with parameterized clouds and convection (Su et al., 2000; Held et al., 2007; Popke et al., 2013; Becker and Stevens, 2014; Reed et al., 2015).”
Convective Self-Aggregation in Numerical Simulations: A Review (2017, background): “…Stephens et al, 2008; Wing and Cronin, 2016), and regional/global models with parameterized clouds and convection (Su et al, 2000; Held et al, 2007; Popke et al, 2013; Becker and Stevens, 2014; Reed et al, 2015; Arnold and Randall, 2015; Reed and Medeiros, 2016; Coppin and Bony, 2015; Silvers et…”