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Evaluating the Role of Atmospheric Stability in Generating Asymmetrical Precipitation During the Landfall of Hurricane Florence (2018)

dc.contributor.authorMorrison, Lindsey Paigeen
dc.contributor.committeechairZick, Stephanie E.en
dc.contributor.committeememberEllis, Andrewen
dc.contributor.committeememberRamseyer, Craig A.en
dc.contributor.departmentGeographyen
dc.date.accessioned2021-01-12T09:01:00Zen
dc.date.available2021-01-12T09:01:00Zen
dc.date.issued2021-01-11en
dc.description.abstractHurricane Florence (2018) was unique due to its slow storm motion during landfall, causing convective rainbands to produce high amounts of precipitation along the coast of North Carolina. This study focuses on the relationship between precipitation asymmetries and atmospheric stability surrounding the tropical cyclone (TC) during the landfall period of a nearly-stationary TC. Previous research with idealized hurricane simulations suggests that atmospheric stability may vary surrounding a TC during landfall, with the atmosphere destabilizing offshore and stabilizing onshore. However, this finding has not been studied using a realistic approach. Due to Hurricane Florence's slow motion, the storm was situated at the land-ocean boundary for multiple days, providing an ideal opportunity to examine the role of atmospheric stability in modifying hurricane precipitation during landfall. This study uses the Advanced Research Weather Research and Forecasting (WRF-ARW) version 3.6.1 to produce high-resolution simulations to examine the variations in precipitation and atmospheric stability surrounding Hurricane Florence. Precipitation accumulation at different temporal scales was used to determine that asymmetries existed during the landfall period. Observed and model-simulated Convective Available Potential Energy (CAPE) were used to measure stability surrounding the TC. Simulated CAPE indicates that there was a significant difference between stability right- and left-of-track. In addition to a control simulation, two experimental simulations were conducted by modifying the land surface to vary the heat and moisture exchange coefficient (HS) and hold the surface roughness (Z0) constant. By isolating the HS to be more moist or dry, the altered low-level moisture was hypothesized to cause the precipitation and convection distributions to become more symmetrical or asymmetrical, respectively. The results from the experimental simulations showed that the altered land surface affects the relative humidity from the surface to 950 mb, which has an immediate impact on stability off-shore left-of-track. Overall, the precipitation and stability asymmetries were not significantly impacted by the altered near-surface moisture, indicating other physical factors contribute to the asymmetries. The results of this study provide insight into the role of atmospheric instability in generating asymmetrical precipitation distributions in landfalling TCs, which may be particularly important in slow-moving TCs like Hurricane Florence.en
dc.description.abstractgeneralLandfalling tropical weather systems such as hurricanes can significantly impact coastal communities due to severe flooding and damaging winds. Hurricane Florence (2018) affected coastal and inland communities in North Carolina and South Carolina when the storm produced a significant amount of precipitation over the coastal region. During landfall, the center of Hurricane Florence moved slowly parallel to the coastline, which creates a suitable time frame to isolate and study the influence of landfall on precipitation asymmetries. Precipitation asymmetry occurs when more rainfall falls on one side of the hurricane; for example, heavier precipitation tends to occur on the right side of a hurricane during the landfall period. Hurricane rainbands that are responsible for producing heavy precipitation form in areas where there is higher moisture near the surface while lighter precipitation forms in areas where there is drier air near the surface. This study focuses on the relationship between land surface moisture and spatial variations of precipitation during the hurricane landfall period by studying observations and model simulations of Hurricane Florence. The model simulation of Hurricane Florence found that more precipitation fell on the right side of the storm, indicating that there was precipitation asymmetry. In order to understand how the precipitation asymmetries form, the model simulation of Hurricane Florence was modified to create two experiments. In the first experiment, the land surface was altered to have a moister land surface, which should cause the hurricane precipitation to be more symmetrical. In the second experiment, the land surface was altered to have a drier land surface, which should cause stronger precipitation asymmetry. However, the results did not match this expectation. Instead, both experiments simulated asymmetrical precipitation with more precipitation falling on the right side of each storm during the landfall period. These results suggest that the modified land surface moisture did not have a significant impact on the formation of precipitation asymmetries. Other factors are therefore suggested to have a more dominant influence on the development of precipitation. Overall, this work can support future studies by ruling out the impact of land surface moisture on a hurricane's precipitation formation during the landfall period.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:28875en
dc.identifier.urihttp://hdl.handle.net/10919/101846en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjecttropical cycloneen
dc.subjecthurricaneen
dc.subjectprecipitationen
dc.subjectconvectionen
dc.subjectatmospheric stabilityen
dc.titleEvaluating the Role of Atmospheric Stability in Generating Asymmetrical Precipitation During the Landfall of Hurricane Florence (2018)en
dc.typeThesisen
thesis.degree.disciplineGeographyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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