Dataset Information

Efficient In-Cloud Removal of Aerosols by Deep Convection.

ABSTRACT: Convective systems dominate the vertical transport of aerosols and trace gases. The most recent in situ aerosol measurements presented here show that the concentrations of primary aerosols including sea salt and black carbon drop by factors of 10 to 10,000 from the surface to the upper troposphere. In this study we show that the default convective transport scheme in the National Science Foundation/Department of Energy Community Earth System Model results in a high bias of 10-1,000 times the measured aerosol mass for black carbon and sea salt in the middle and upper troposphere. A modified transport scheme, which considers aerosol activation from entrained air above the cloud base and aerosol-cloud interaction associated with convection, dramatically improves model agreement with in situ measurements suggesting that deep convection can efficiently remove primary aerosols. We suggest that models that fail to consider secondary activation may overestimate black carbon's radiative forcing by a factor of 2.

SUBMITTER: Yu P

PROVIDER: S-EPMC8243348 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Efficient In-Cloud Removal of Aerosols by Deep Convection.

Yu Pengfei P Yu Pengfei P Froyd Karl D KD Portmann Robert W RW Toon Owen B OB Freitas Saulo R SR Bardeen Charles G CG Brock Charles C Fan Tianyi T Gao Ru-Shan RS Katich Joseph M JM Kupc Agnieszka A Liu Shang S Maloney Christopher C Murphy Daniel M DM Rosenlof Karen H KH Schill Gregory G Schwarz Joshua P JP Williamson Christina C

Geophysical research letters 20190123 2

Convective systems dominate the vertical transport of aerosols and trace gases. The most recent in situ aerosol measurements presented here show that the concentrations of primary aerosols including sea salt and black carbon drop by factors of 10 to 10,000 from the surface to the upper troposphere. In this study we show that the default convective transport scheme in the National Science Foundation/Department of Energy Community Earth System Model results in a high bias of 10-1,000 times the mea ...[more]

PMID: 34219825

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Project description:The deep convective cloud-environment feedback loop is likely important to Titan's global methane, energy, and momentum cycles, just as it is for Earth's global water, energy, and momentum budgets. General circulation models of Titan's atmosphere are unable to explicitly simulate deep convection and must instead parameterize the impact of this important subgrid-scale phenomenon on the model-resolved atmospheric state. The goal of this study is to better quantify through cloud resolving modeling the effects of deep convective methane storms on their environment and to feed that information forward to improve parameterizations in global models. Dozens of atmospheric profiles unstable with respect to deep moist convection are extracted from the global Titan Atmospheric Model (TAM) and used to initialize the cloud-resolving Titan Regional Atmospheric Modeling System (TRAMS). Mean profiles of heating/cooling and moistening/drying of the large-scale environment in TRAMS indicate that Titan's deep convection forces the environment in a manner analogous to Earth: Large-scale subsidence of the environmental air warms and dries the environment, but clouds can also moisten the environment through the detrainment and evaporation of condensate near cloud top. Relative humidity profiles and characteristic convective time scales are derived to guide the tuning of the deep convective parameterization implemented in TAM, as described in a companion paper. The triggering of convection, the dry convective mixing of the planetary boundary layer, and the entrainment of environmental air into rising air parcels are found to be critical to determining whether a deep convective cloud will form. Only profiles with relatively large convective available potential energy (CAPE) and well mixed planetary boundary layers with high relative humidity were found to produce storms. Environments with low level thermal inversions and planetary boundary layers with low relative humidity or rapidly decreasing moisture with height failed to generate deep convection in TRAMS despite positive CAPE.

Dataset Information

Efficient In-Cloud Removal of Aerosols by Deep Convection.

Publications

Efficient In-Cloud Removal of Aerosols by Deep Convection.

Similar Datasets

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