DEEP CONVECTIVE TRANSPORT AND WET SCAVENGING IN DIFFERENT CONVECTIVE REGIMES DURING THE DC3 FIELD CAMPAIGN

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dc.contributor.advisorPickering, Kennethen_US
dc.contributor.authorLi, Yunyaoen_US
dc.contributor.departmentAtmospheric and Oceanic Sciencesen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2018-09-15T05:35:47Z
dc.date.available2018-09-15T05:35:47Z
dc.date.issued2018en_US
dc.description.abstractDeep convective transport of surface moisture and pollution from the planetary boundary layer to the upper troposphere and lower stratosphere affects the radiation budget and climate. Firstly, I analyzed the deep convective transport through cloud-resolved simulations of three different convective regimes from the 2012 Deep Convective Clouds and Chemistry (DC3) field campaign: an airmass thunderstorm, a supercell storm, and a mesoscale convective system (MCS). Analysis of vertical flux divergence shows that deep convective transport in the supercell case is the strongest per unit area, while transport of boundary layer insoluble trace gases is relatively weak in the MCS due to the injection of clean air into the mid-troposphere by a strong rear inflow jet. Additionally, forward and backward trajectories are used to determine the source of the upper-level detrained air. My second focus is using of cloud parameterized Weather Research and Forecasting model coupled with chemistry (WRF-Chem) simulations to analyze the subgrid deep convective transport in the supercell case and MCS case. Based on the precipitation results, the best WRF simulation of these storms was obtained with use of the Grell-Freitas (GF) convective scheme. The default subgrid convective transport scheme was replaced with a scheme to compute convective transport within the GF subgrid cumulus parameterization, which resulted in improved transport simulations. The results demonstrate the importance of having subgrid convective transport consistent with the convective parameterization in regional models. Moreover, the subgrid scale convective transport played a more significant role in the supercell case than the MCS case. I evaluated the model-simulated subgrid wet scavenging of soluble trace gases (such as HNO3, CH2O, CH3OOH, H2O2, and SO2) in the supercell case, and improved subgrid wet scavenging by determining appropriate ice retention factors, and by adjusting the conversion rate of cloud water to rain water. The introduction of the ice retention factors greatly improved the model simulation of less soluble species (e.g. decreased the CH2O simulation error by 12 % and decreased the CH3OOH simulation error by 63%). Finally, I conducted a > 24-hour long simulation to examine downwind ozone production and its sensitivity to the ice retention factors.en_US
dc.identifierhttps://doi.org/10.13016/M2GB1XM3H
dc.identifier.urihttp://hdl.handle.net/1903/21401
dc.language.isoenen_US
dc.subject.pqcontrolledAtmospheric sciencesen_US
dc.subject.pqcontrolledAtmospheric chemistryen_US
dc.subject.pquncontrolledCloud parameterizationen_US
dc.subject.pquncontrolledDeep convective transporten_US
dc.subject.pquncontrolledTrace gasesen_US
dc.subject.pquncontrolledWet scavengingen_US
dc.subject.pquncontrolledWRF-Chemen_US
dc.titleDEEP CONVECTIVE TRANSPORT AND WET SCAVENGING IN DIFFERENT CONVECTIVE REGIMES DURING THE DC3 FIELD CAMPAIGNen_US
dc.typeDissertationen_US

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