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Examining chaotic convection with super-parameterization ensembles

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dc.contributor.authorJones, Todd R., author
dc.contributor.authorRandall, David A., advisor
dc.contributor.authorKummerow, Christian D., committee member
dc.contributor.authorVan den Heever, Susan S., committee member
dc.contributor.authorSchumacher, Russ S., committee member
dc.contributor.authorEykholt, Richard E., committee member
dc.date.accessioned2017-06-09T15:41:03Z
dc.date.available2017-06-09T15:41:03Z
dc.date.issued2017
dc.description.abstractThis study investigates a variety of features present in a new configuration of the Community Atmosphere Model (CAM) variant, SP-CAM 2.0. The new configuration (multiple-parameterization-CAM, MP-CAM) changes the manner in which the super-parameterization (SP) concept represents physical tendency feedbacks to the large-scale by using the mean of 10 independent two-dimensional cloud-permitting model (CPM) curtains in each global model column instead of the conventional single CPM curtain. The climates of the SP and MP configurations are examined to investigate any significant differences caused by the application of convective physical tendencies that are more deterministic in nature, paying particular attention to extreme precipitation events and large-scale weather systems, such as the Madden-Julian Oscillation (MJO). A number of small but significant changes in the mean state climate are uncovered, and it is found that the new formulation degrades MJO performance. Despite these deficiencies, the ensemble of possible realizations of convective states in the MP configuration allows for analysis of uncertainty in the small-scale solution, lending to examination of those weather regimes and physical mechanisms associated with strong, chaotic convection. Methods of quantifying precipitation predictability are explored, and use of the most reliable of these leads to the conclusion that poor precipitation predictability is most directly related to the proximity of the global climate model column state to atmospheric critical points. Secondarily, the predictability is tied to the availability of potential convective energy, the presence of mesoscale convective organization on the CPM grid, and the directive power of the large-scale.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierJones_colostate_0053A_14045.pdf
dc.identifier.urihttp://hdl.handle.net/10217/181330
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectconvection
dc.subjectparameterization
dc.subjectpredictability
dc.subjectmodeling
dc.subjectclimatology
dc.subjectprecipitation
dc.titleExamining chaotic convection with super-parameterization ensembles
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineAtmospheric Science
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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