Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics
Abstract The representation of clouds and organized tropical convection remains one of the biggest sources of uncertainties in climate and long‐term weather prediction models. Some of the most common cumulus parameterization schemes, namely, mass‐flux schemes, rely on the quasi‐equilibrium (QE) clos...
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doaj-7ddf0b38bb3b4f17983bc29a6156a83a2020-11-24T21:56:33ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662019-08-011182474250210.1029/2019MS001627Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic DynamicsBoualem Khouider0Etienne Leclerc1Department of Mathematics and Statistics University of Victoria Victoria British Columbia CanadaDepartment of Mathematics and Statistics University of Victoria Victoria British Columbia CanadaAbstract The representation of clouds and organized tropical convection remains one of the biggest sources of uncertainties in climate and long‐term weather prediction models. Some of the most common cumulus parameterization schemes, namely, mass‐flux schemes, rely on the quasi‐equilibrium (QE) closure, which assumes that convection consumes the large‐scale instability and restores large‐scale equilibrium instantaneously. However, the QE hypothesis has been challenged both conceptually and in practice. Subsequently, the QE assumption was relaxed, and instead, prognostic equations for the cloud work function (CWF) and the cumulus kinetic energy (CKE) were derived and used. It was shown that even if the CWF kernel serves to damp the CWF, the prognostic system exhibits damped oscillations on a timescale of a few hours, giving parameterized‐cumulus‐clouds enough memory to interact with each other, with the environment, and with stratiform anvils in particular. Herein, we show that when cloud‐cloud interactions are reintroduced into the CWF‐CKE equations, the coupled system becomes unstable. Moreover, we couple the CWF‐CKE prognostic equations to dynamical equations for the cloud area fractions, based on the mean field limit of a stochastic multicloud model. Qualitative analysis and numerical simulations show that the CKE‐CWF‐cloud area fraction equations exhibit interesting dynamics including multiple equilibria, limit cycles, and chaotic behavior both when the large‐scale forcing is held fixed and when it oscillates with various frequencies. This is representative of cumulus convection variability, and its capability to transition between various regimes of organization at multiple scales and regimes of scattered convection, in an intermittent and chaotic fashion.https://doi.org/10.1029/2019MS001627cumulus parameterizationmass fluxprognostic closuremultiple equilibriacloud area fractionchaotic dynamics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Boualem Khouider Etienne Leclerc |
spellingShingle |
Boualem Khouider Etienne Leclerc Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics Journal of Advances in Modeling Earth Systems cumulus parameterization mass flux prognostic closure multiple equilibria cloud area fraction chaotic dynamics |
author_facet |
Boualem Khouider Etienne Leclerc |
author_sort |
Boualem Khouider |
title |
Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics |
title_short |
Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics |
title_full |
Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics |
title_fullStr |
Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics |
title_full_unstemmed |
Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics |
title_sort |
toward a stochastic relaxation for the quasi‐equilibrium theory of cumulus parameterization: multicloud instability, multiple equilibria, and chaotic dynamics |
publisher |
American Geophysical Union (AGU) |
series |
Journal of Advances in Modeling Earth Systems |
issn |
1942-2466 |
publishDate |
2019-08-01 |
description |
Abstract The representation of clouds and organized tropical convection remains one of the biggest sources of uncertainties in climate and long‐term weather prediction models. Some of the most common cumulus parameterization schemes, namely, mass‐flux schemes, rely on the quasi‐equilibrium (QE) closure, which assumes that convection consumes the large‐scale instability and restores large‐scale equilibrium instantaneously. However, the QE hypothesis has been challenged both conceptually and in practice. Subsequently, the QE assumption was relaxed, and instead, prognostic equations for the cloud work function (CWF) and the cumulus kinetic energy (CKE) were derived and used. It was shown that even if the CWF kernel serves to damp the CWF, the prognostic system exhibits damped oscillations on a timescale of a few hours, giving parameterized‐cumulus‐clouds enough memory to interact with each other, with the environment, and with stratiform anvils in particular. Herein, we show that when cloud‐cloud interactions are reintroduced into the CWF‐CKE equations, the coupled system becomes unstable. Moreover, we couple the CWF‐CKE prognostic equations to dynamical equations for the cloud area fractions, based on the mean field limit of a stochastic multicloud model. Qualitative analysis and numerical simulations show that the CKE‐CWF‐cloud area fraction equations exhibit interesting dynamics including multiple equilibria, limit cycles, and chaotic behavior both when the large‐scale forcing is held fixed and when it oscillates with various frequencies. This is representative of cumulus convection variability, and its capability to transition between various regimes of organization at multiple scales and regimes of scattered convection, in an intermittent and chaotic fashion. |
topic |
cumulus parameterization mass flux prognostic closure multiple equilibria cloud area fraction chaotic dynamics |
url |
https://doi.org/10.1029/2019MS001627 |
work_keys_str_mv |
AT boualemkhouider towardastochasticrelaxationforthequasiequilibriumtheoryofcumulusparameterizationmulticloudinstabilitymultipleequilibriaandchaoticdynamics AT etienneleclerc towardastochasticrelaxationforthequasiequilibriumtheoryofcumulusparameterizationmulticloudinstabilitymultipleequilibriaandchaoticdynamics |
_version_ |
1725858415523135488 |