Universität zu Köln

Sakradzija, M., Seifert, A. and Heus, T. (2015). Fluctuations in a quasi-stationary shallow cumulus cloud ensemble. Nonlinear Process Geophys., 22 (1). S. 65 - 86. GOTTINGEN: COPERNICUS GESELLSCHAFT MBH. ISSN 1023-5809

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Abstract

We propose an approach to stochastic parameterisation of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a large eddy simulation (LES) model and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal, due to the different shallow cloud subtypes, active and passive clouds. Each distribution mode can be approximated using a Weibull distribution, which is a generalisation of exponential distribution by accounting for the change in distribution shape due to the diversity of cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterisation is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive -the smaller the grid size, the broader the distribution.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Sakradzija, M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Seifert, A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Heus, T. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-419569
DOI:	10.5194/npg-22-65-2015
Journal or Publication Title:	Nonlinear Process Geophys.
Volume:	22
Number:	1
Page Range:	S. 65 - 86
Date:	2015
Publisher:	COPERNICUS GESELLSCHAFT MBH
Place of Publication:	GOTTINGEN
ISSN:	1023-5809
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language LARGE-EDDY SIMULATIONS; EQUILIBRIUM CONVECTIVE ENSEMBLE; STOCHASTIC PARAMETERIZATION; MESOSCALE PREDICTABILITY; PREDICTION SYSTEM; PART II; CLIMATE PREDICTION; RESOLVING MODEL; BOUNDARY-LAYER; PARAMETRIZATION Multiple languages Geosciences, Multidisciplinary; Mathematics, Interdisciplinary Applications; Meteorology & Atmospheric Sciences; Physics, Fluids & Plasmas Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/41956