Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs

Abstract The radiative‐convective equilibrium (RCE) of two models exhibiting convective aggregation has been compared. The goal of the work, following the suggestion from the RCE Model Intercomparison Project (RCEMIP), is to identify key parameters controlling self‐aggregation in RCE for both models...

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Main Authors: P. Bongioannini Cerlini, M. Saraceni, L. Silvestri
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2023-02-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
Online Access:https://doi.org/10.1029/2022MS003323
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author P. Bongioannini Cerlini
M. Saraceni
L. Silvestri
author_facet P. Bongioannini Cerlini
M. Saraceni
L. Silvestri
author_sort P. Bongioannini Cerlini
collection DOAJ
description Abstract The radiative‐convective equilibrium (RCE) of two models exhibiting convective aggregation has been compared. The goal of the work, following the suggestion from the RCE Model Intercomparison Project (RCEMIP), is to identify key parameters controlling self‐aggregation in RCE for both models, to discuss the processes controlled by these parameters and to underline the models similarities and differences. The two cloud resolving models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), present similar statistics concerning precipitation, but different warming, and drying of the atmosphere, within the spread of the RCEMIP values. On the other hand, the two models show different strengths of the moisture feedback, due to the different saturation of the sub‐cloud layer. A saturated sub‐cloud layer in ARPS (which was not artificially imposed in the numerical setup) allows the localization of convection in moist regions, by weakening the negative influence of cold pools. Such a mechanism leads to a lower degree of aggregation (based on three organization metrics) and a weaker effect of the organized state on the average domain statistics in ARPS. Stronger cold pools in SAM, instead, help the creation of shallow clouds in dry regions, increasing the longwave feedback responsible for their expansion; while delocalizing convection in moist regions and therefore opposing high‐cloud radiative‐feedback. Further experiments are needed to generalize such findings to other RCEMIP models, also investigating the role of microphysics and turbulence schemes in regulating such mechanisms.
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spelling doaj.art-ad0deac671dd482483294f0a012c99a92023-10-10T14:00:44ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662023-02-01152n/an/a10.1029/2022MS003323Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMsP. Bongioannini Cerlini0M. Saraceni1L. Silvestri2Centro Interuniversitario di Ricerca sull'Inquinamento e sull'Ambiente Mauro Felli (CIRIAF)—Centro di Ricerca sul Clima e Cambiamenti Climatici (CRC) University of Perugia Perugia ItalyDepartment of Civil and Environmental Engineering (DICA)—Centro di Ricerca sul Clima e Cambiamenti Climatici (CRC) University of Perugia Perugia ItalyDepartment of Civil and Environmental Engineering (DICA)—Centro di Ricerca sul Clima e Cambiamenti Climatici (CRC) University of Perugia Perugia ItalyAbstract The radiative‐convective equilibrium (RCE) of two models exhibiting convective aggregation has been compared. The goal of the work, following the suggestion from the RCE Model Intercomparison Project (RCEMIP), is to identify key parameters controlling self‐aggregation in RCE for both models, to discuss the processes controlled by these parameters and to underline the models similarities and differences. The two cloud resolving models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), present similar statistics concerning precipitation, but different warming, and drying of the atmosphere, within the spread of the RCEMIP values. On the other hand, the two models show different strengths of the moisture feedback, due to the different saturation of the sub‐cloud layer. A saturated sub‐cloud layer in ARPS (which was not artificially imposed in the numerical setup) allows the localization of convection in moist regions, by weakening the negative influence of cold pools. Such a mechanism leads to a lower degree of aggregation (based on three organization metrics) and a weaker effect of the organized state on the average domain statistics in ARPS. Stronger cold pools in SAM, instead, help the creation of shallow clouds in dry regions, increasing the longwave feedback responsible for their expansion; while delocalizing convection in moist regions and therefore opposing high‐cloud radiative‐feedback. Further experiments are needed to generalize such findings to other RCEMIP models, also investigating the role of microphysics and turbulence schemes in regulating such mechanisms.https://doi.org/10.1029/2022MS003323cloud resolving modelsself‐aggregationmoisture‐convectioncold poolssub‐cloud layerstatistical equilibrium
spellingShingle P. Bongioannini Cerlini
M. Saraceni
L. Silvestri
Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs
Journal of Advances in Modeling Earth Systems
cloud resolving models
self‐aggregation
moisture‐convection
cold pools
sub‐cloud layer
statistical equilibrium
title Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs
title_full Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs
title_fullStr Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs
title_full_unstemmed Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs
title_short Competing Effect of Radiative and Moisture Feedback in Convective Aggregation States in Two CRMs
title_sort competing effect of radiative and moisture feedback in convective aggregation states in two crms
topic cloud resolving models
self‐aggregation
moisture‐convection
cold pools
sub‐cloud layer
statistical equilibrium
url https://doi.org/10.1029/2022MS003323
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AT msaraceni competingeffectofradiativeandmoisturefeedbackinconvectiveaggregationstatesintwocrms
AT lsilvestri competingeffectofradiativeandmoisturefeedbackinconvectiveaggregationstatesintwocrms