Editorial Type:
Article
Article Type:
Research Article

Stochastic Behavior of Tropical Convection in Observations and a Multicloud Model

Karsten Peters ARC Centre of Excellence for Climate System Science, School of Mathematical Sciences, Monash University, Clayton, Victoria, Australia

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Christian Jakob ARC Centre of Excellence for Climate System Science, School of Mathematical Sciences, Monash University, Clayton, Victoria, Australia

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Laura Davies School of Mathematical Sciences, Monash University, Clayton, Victoria, Australia

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Boualem Khouider Department of Mathematics and Statistics, University of Victoria, Victoria, British Columbia, Canada

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Andrew J. Majda Centre for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, New York University, New York, New York

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Print Publication:
01 Nov 2013
DOI:
https://doi.org/10.1175/JAS-D-13-031.1
Page(s):
3556–3575
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Abstract

The aim for a more accurate representation of tropical convection in global circulation models is a long-standing issue. Here, the relationships between large and convective scales in observations and a stochastic multicloud model (SMCM) to ultimately support the design of a novel convection parameterization with stochastic elements are investigated. Observations of tropical convection obtained at Darwin and Kwajalein are used here. It is found that the variability of observed tropical convection generally decreases with increasing large-scale forcing, implying a transition from stochastic to more deterministic behavior with increasing forcing. Convection shows a more systematic relationship with measures related to large-scale convergence compared to measures related to energetics (e.g., CAPE). Using the observations, the parameters in the SMCM are adjusted. Then, the SMCM is forced with the time series of the observed large-scale state and the simulated convective behavior is compared to that observed. It is found that the SMCM cloud fields compare better with observations when using predictors related to convergence rather than energetics. Furthermore, the underlying framework of the SMCM is able to reproduce the observed functional dependencies of convective variability on the imposed large-scale state—an encouraging result on the road toward a novel convection parameterization approach. However, establishing sound cause-and-effect relationships between tropical convection and the large-scale environment remains problematic and warrants further research.

Corresponding author address: Karsten Peters, ARC Centre of Excellence for Climate System Science, School of Mathematical Sciences, Monash University, Clayton, VIC 3800, Australia. E-mail: karsten.peters@monash.edu

Abstract

The aim for a more accurate representation of tropical convection in global circulation models is a long-standing issue. Here, the relationships between large and convective scales in observations and a stochastic multicloud model (SMCM) to ultimately support the design of a novel convection parameterization with stochastic elements are investigated. Observations of tropical convection obtained at Darwin and Kwajalein are used here. It is found that the variability of observed tropical convection generally decreases with increasing large-scale forcing, implying a transition from stochastic to more deterministic behavior with increasing forcing. Convection shows a more systematic relationship with measures related to large-scale convergence compared to measures related to energetics (e.g., CAPE). Using the observations, the parameters in the SMCM are adjusted. Then, the SMCM is forced with the time series of the observed large-scale state and the simulated convective behavior is compared to that observed. It is found that the SMCM cloud fields compare better with observations when using predictors related to convergence rather than energetics. Furthermore, the underlying framework of the SMCM is able to reproduce the observed functional dependencies of convective variability on the imposed large-scale state—an encouraging result on the road toward a novel convection parameterization approach. However, establishing sound cause-and-effect relationships between tropical convection and the large-scale environment remains problematic and warrants further research.

Corresponding author address: Karsten Peters, ARC Centre of Excellence for Climate System Science, School of Mathematical Sciences, Monash University, Clayton, VIC 3800, Australia. E-mail: karsten.peters@monash.edu
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