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dc.contributor.advisorRandall, David A.
dc.contributor.authorJones, Todd R.
dc.contributor.committeememberKummerow, Christian D.
dc.contributor.committeememberVan den Heever, Susan S.
dc.contributor.committeememberSchumacher, Russ C.
dc.contributor.committeememberEykholt, Richard E.
dc.date.accessioned2017-06-09T15:41:03Z
dc.date.available2017-06-09T15:41:03Z
dc.date.issued2017
dc.description2017 Spring.
dc.descriptionIncludes bibliographical references.
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.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019 - CSU Theses and Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectconvection
dc.subjectparameterization
dc.subjectpredictability
dc.subjectmodeling
dc.subjectclimatology
dc.subjectprecipitation
dc.titleExamining chaotic convection with super-parameterization ensembles
dc.typeText
dcterms.rights.dplaThe copyright and related rights status of this Item has not been evaluated (https://rightsstatements.org/vocab/CNE/1.0/). Please refer to the organization that has made the Item available for more information.
thesis.degree.disciplineAtmospheric Science
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)


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