4.6 Article

Coupled radiative convective equilibrium simulations with explicit and parameterized convection

期刊

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/2016MS000666

关键词

RCE; convection-permitting; convective parameterization; organization; climate

资金

  1. Max Planck Society for advancement of science
  2. Hans Ertel Centre for Weather Research
  3. BMVBS (Federal Ministry of Transport, Building and Urban Development)

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Radiative convective equilibrium has been applied in past studies to various models given its simplicity and analogy to the tropical climate. At convection-permitting resolution, the focus has been on the organization of convection that appears when using fixed sea surface temperature (SST). Here the SST is allowed to freely respond to the surface energy. The goals are to examine and understand the resulting transient behavior, equilibrium state, and perturbations thereof, as well as to compare these results to a simulation integrated with parameterized cloud and convection. Analysis shows that the coupling between the SST and the net surface energy acts to delay the onset of self-aggregation and may prevent it, in our case, for a slab ocean of less than 1 m. This is so because SST gradients tend to oppose the shallow low-level circulation that is associated with the self-aggregation of convection. Furthermore, the occurrence of self-aggregation is found to be necessary for reaching an equilibrium state and avoiding a greenhouse-like climate. In analogy to the present climate, the self-aggregation generates the dry and clear subtropics that allow the system to efficiently cool. In contrast, strong shortwave cloud radiative effects, much stronger than at convection-permitting resolution, prevent the simulation with parameterized cloud and convection to fall into a greenhouse state. The convection-permitting simulations also suggest that cloud feedbacks, as arising when perturbing the equilibrium state, may be very different, and in our case less negative, than what emerges from general circulation models.

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