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dc.identifier.urihttp://hdl.handle.net/11401/77770
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeDissertation
dcterms.abstractMicrophysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.
dcterms.available2017-09-20T16:53:33Z
dcterms.contributorZhang, Minghuaen_US
dcterms.contributorChang, Edmunden_US
dcterms.contributorKhairoutdinov, Maraten_US
dcterms.contributorVogelmann, Andrewen_US
dcterms.contributorGolaz, Chrisen_US
dcterms.contributor.en_US
dcterms.creatorXie, Xin
dcterms.dateAccepted2017-09-20T16:53:33Z
dcterms.dateSubmitted2017-09-20T16:53:33Z
dcterms.descriptionDepartment of Marine and Atmospheric Scienceen_US
dcterms.extent103 pg.en_US
dcterms.formatMonograph
dcterms.formatApplication/PDFen_US
dcterms.identifierhttp://hdl.handle.net/11401/77770
dcterms.issued2017-05-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2017-09-20T16:53:33Z (GMT). No. of bitstreams: 1 Xie_grad.sunysb_0771E_13231.pdf: 11411105 bytes, checksum: d5f717b72a87cabc2c99f0831bd8804f (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectAtmospheric sciences
dcterms.subjectconvection parameterization, subgrid inhomogeneity
dcterms.titleImproving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme
dcterms.typeDissertation


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