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Diabatic Processes Modifying the Structure and Evolution of Idealized Baroclinic Life Cycle Simulations

Diabatic processes including latent heating and radiation are parameterized in numerical weather prediction (NWP) models and constitute a major source of error. Isolating the extent of diabatic modification in an extratropical cyclone in observational atmospheric data is difficult. This study analyzes four idealized Advanced Weather Research and Forecasting (WRF-ARW) model sensitivity experiments in which radiation or moisture are either included or withheld. The experiments consist of the following: no radiation and no moisture (NRNM), radiation and no moisture (RNM), moisture and no radiation (NRM), and radiation and moisture (RM). Simulations are of an idealized baroclinic wave in the midlatitudes. Because baroclinic waves are associated with synoptic scale weather events, these WRF-ARW simulations are the ideal platform to better understand the interactions of diabatic and dynamic processes. Inclusion of moisture and radiation has a significant impact on baroclinic wave structure and evolution. On the synoptic scale, the RM experiment demonstrates greatest amplification/depth, earliest growth, and was the only experiment with cyclonic breaking in the troposphere and high amplitude anticyclonic breaking in the lower stratosphere. On the sub-synoptic scale, vertical dipoles in isentropic potential vorticity (IPV) and cloud-scale anomalies developed in the middle to upper troposphere as the wave matured. While radiation alone yields no anomaly, and moisture alone yields a small anomaly, the inclusion of radiation and moisture together yields a significantly larger IPV anomaly. Anomalies may be due to constructive interference or nonlinear feedbacks between radiative cooling and latent heating. Results of this study have important implications for NWP, especially in the representation of physical processes via parameterization schemes. Knowledge gained about physical processes and their feedbacks on resolved flow might help to better understand error and bias in NWP models. / A Thesis submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2016. / June 28, 2016. / Includes bibliographical references. / Jeffrey M. Chagnon, Professor Directing Thesis; Ming Cai, Outside Committee Member; Guosheng Liu, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_366062
ContributorsGlasser, Daisy (authoraut), Chagnon, Jeffrey M. (professor directing thesis), Cai, Ming, 1957- (outside committee member), Liu, Guosheng (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Earth, Ocean, and Atmospheric Science (degree granting department)
PublisherFlorida State University, Florida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text
Format1 online resource (53 pages), computer, application/pdf
RightsThis Item is protected by copyright and/or related rights. 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). The copyright in theses and dissertations completed at Florida State University is held by the students who author them.

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