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Improving the representation of shallow cumulus convection with the Simplified Higher-Order Closure Mass-Flux (SHOC+MF v1.0) approach.

Authors :
Chinita, Maria J.
Witte, Mikael
Kurowski, Marcin J.
Teixeira, Joao
Suselj, Kay
Matheou, Georgios
Bogenschutz, Peter
Source :
Geoscientific Model Development Discussions. 9/6/2022, p1-23. 23p.
Publication Year :
2022

Abstract

Parameterized boundary layer turbulence and moist convection remain some of the largest sources of uncertainty in general circulation models. High-resolution climate modeling aims to reduce that uncertainty by explicitly attempting to resolve deep moist convective motions. An example of such a model is the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) with a target global resolution of 3.25 km, allowing for a more accurate representation of complex mesoscale deep convective dynamics. Yet, small-scale planetary boundary layer turbulence and shallow convection still need to be parameterized, which in SCREAM is accomplished through the TKE-based Simplified Higher-Order Closure (SHOC)--a simplified version of the assumed doubled-Gaussian PDF higher-order closure method. In this paper, we implement a stochastic multiplume Mass-Flux (MF) parameterization of dry and shallow convection in SCREAM to go beyond the limitations of double-Gaussian PDF closures and couple it to SHOC (SHOC+MF). The new parameterization implemented in a single-column model type version of SCREAM produces results for two shallow cumulus convection cases (marine and continental shallow convection) that agree well with the reference large-eddy simulation data, thus improving the general representation of the thermodynamic quantities and their turbulent fluxes as well as cloud macrophysics in the model. Furthermore, SHOC+MF parameterization shows weak sensitivity to the vertical grid resolution and model time step. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19919611
Database :
Academic Search Index
Journal :
Geoscientific Model Development Discussions
Publication Type :
Academic Journal
Accession number :
159073427
Full Text :
https://doi.org/10.5194/gmd-2022-162