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Convective memory, and the role of cold pools

Abstract : Convective parameterizations struggle to represent the spatiotemporal variability of convection. This may be because they assume that convection can be diagnosed from the large-scale state, without knowing the convective history. The concept of convective memory, which states that convection depends on its own history, could help overcome this issue. A new framework suggests a distinction between microstate (unresolved) memory and macrostate (large-scale) memory. Using a hierarchy of models either in Radiative-Convective Equilibrium or under fixed-macrostate conditions, the thesis analyses the recovery to homogenisation perturbations. It exploits a Cloud-Resolving Model, a General Circulation Model (GCM) in 1D and in 3D, and a simple predator-prey model. The results show that convective memory plays a role on time scales of up to a day. Convective memory in time is dramatically enhanced by convective organisation in space. Microstate memory is found to be mostly stored in boundary layer microstate structures of water vapour and temperature, with a dominant water vapour memory. Furthermore, the convective microstate is shown to be inherently unstable, which confirms that knowledge of the macrostate conditions is not sufficient to predict convection. The standard version of the GCM already shows a reasonable level of convective persistence. A simple modification of the GCM convection scheme, meant to improve cold pools over oceans, makes cold pools less cold and thus weaker to trigger convection. This leads to more intermittent precipitation, partly correcting a typical GCM bias. Overall the thesis fosters introducing prognostic variables into GCMs and suggests ways to do it.
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Submitted on : Thursday, June 11, 2020 - 12:15:41 PM
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  • HAL Id : tel-02864797, version 1

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Maxime Colin. Convective memory, and the role of cold pools. Meteorology. Sorbonne Université, 2018. English. ⟨NNT : 2018SORUS312⟩. ⟨tel-02864797⟩

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