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Properties of the tropical hydrologic cycle as analyzed through 3-dimensional k-means cluster analysis

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dc.contributor.authorRogers, Matthew Alan, author
dc.contributor.authorStephens, Graeme, advisor
dc.date.accessioned2024-03-13T20:12:33Z
dc.date.available2024-03-13T20:12:33Z
dc.date.issued2008
dc.description.abstractAs the primary locations of deep convective activity and unrestrained tropical wave dynamics, the tropical West Pacific and East Indian oceans are among the most important regions in the tropics. Given that most of the region consists of unpopulated expanses of ocean, observations of tropical atmospheric properties in this important region is exceptionally difficult. Only with the help of satellite observations are we capable of gleaning valuable data from this region, and our utilization of advanced analysis techniques allows us to gain more from these observations then would otherwise be possible. In that vein, this dissertation reports on the use of a unique statistical technique, long known to other fields of research, as applied to a combined-instrument satellite observation dataset over the warm pool region of the tropical West Pacific ocean. The statistical technique, known as k-means cluster analysis, is used to delineate self-similar populations of cloud type, hereafter referred to as cloud regimes, from frequency-distribution histograms of cloud-top height, cloud optical thickness, and rainfall amount. We will show that four primary cloud regimes exist in the tropical region discussed, that the four regimes vary primarily through differences in convective activity, and that these four cloud regimes exist in a coherent temporal structure that explains the long-observed variability in convective activity seen in the tropics. Combining this regime information with satellite observations, along with reanalysis data, we then examine the individual properties of each cloud regime. These observations give us the means to understand the forcings behind cloud regime change in the region. We confirm the structural properties of these regimes using analysis from a cloud-resolving model, and apply our new understanding of the mechanism behind this large-scale forcing to the governance of the tropical hydrologic cycle as a whole. The insights gained from this analysis have benefits to both the fields of atmospheric remote sensing, and of cloud- and climate modeling of the tropical atmosphere. Applications of this technique are of particular interest to researchers developing retrieval algorithms for latent heat profiles using active sensors such as the cloud-profiling radar aboard CloudSat.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierETDF_Rogers_2008_3332703.pdf
dc.identifier.urihttps://hdl.handle.net/10217/237931
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.rights.licensePer the terms of a contractual agreement, all use of this item is limited to the non-commercial use of Colorado State University and its authorized users.
dc.subjectcloud regimes
dc.subjecthydrologic cycle
dc.subjectlatent heating
dc.subjecttropical convection
dc.subjectatmospheric sciences
dc.titleProperties of the tropical hydrologic cycle as analyzed through 3-dimensional k-means cluster analysis
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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