Browsing by Author "DesRosiers, Alexander J., author"
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Item Open Access Airborne radar quality control and analysis of the rapid intensification of Hurricane Michael (2018)(Colorado State University. Libraries, 2020) DesRosiers, Alexander J., author; Bell, Michael M., advisor; Barnes, Elizabeth, committee member; Chen, Suren, committee memberImprovements made by the National Hurricane Center (NHC) in track forecasts have outpaced advances in intensity forecasting. Rapid intensification (RI), an increase of at least 30 knots in the maximum sustained winds of a tropical cyclone (TC) in a 24 hour period, is poorly understood and provides a considerable hurdle to intensity forecasting. RI depends on internal processes which require detailed inner core information to better understand. Close range measurements of TCs from aircraft reconnaissance with tail Doppler radar (TDR) allow for the retrieval of the kinematic state of the inner core. Fourteen consecutive passes were flown through Hurricane Michael (2018) as it underwent RI on its way to landfall at category 5 intensity. The TDR data collected offered an exceptional opportunity to diagnose mechanisms that contributed to RI. Quality Control (QC) is required to remove radar gates originating from non meteorological sources which can impair dual-Doppler wind synthesis techniques. Automation of the time-consuming manual QC process was needed to utilize all TDR data collected in Hurricane Michael in a timely manner. The machine learning (ML) random forest technique was employed to create a generalized QC method for TDR data collected in convective environments. The complex decision making ability of ML offered an advantage over past approaches. A dataset of radar scans from a tornadic supercell, bow echo, and mature and developing TCs collected by the Electra Doppler Radar (ELDORA) containing approximately 87.9 million radar gates was mined for predictors. Previous manual QC performed on the data was used to classify each data point as weather or non-weather. This varied dataset was used to train a model which classified over 99% of the radar gates in the withheld testing data succesfully. Creation of a dual-Doppler analysis from a tropical depression using ML efforts that was comparable to manual QC confirmed the utility of this new method. The framework developed was capable of performing QC on the majority of the TDR data from Hurricane Michael. Analyses of the inner core of Hurricane Michael were used to document inner core changes throughout RI. Angular momentum surfaces moved radially inward and became more vertically aligned over time. The hurricane force wind field expanded radially outward and increased in depth. Intensification of the storm became predominantly axisymmetric as RI progressed. TDR-derived winds are used to infer upper-level processes that influenced RI at the surface. Tilting of ambient horizontal vorticity, created by the decay of tangential winds aloft, by the axisymmetric updraft created a positive vorticity tendency atop the existing vorticity tower. A vorticity budget helped demonstrate how the axisymmetric vorticity tower built both upward and outward in the sloped eyewall. A retrieval of the radial gradient of density temperature provided evidence for an increasing warm core temperature perturbation in the eye. Growth of the warm core temperature perturbation in upper levels aided by subsidence helped lower the minimum sea level pressure which correlated with intensification of the near-surface wind field.Item Open Access From surface to tropopause: on the vertical structure of the tropical cyclone vortex(Colorado State University. Libraries, 2024) DesRosiers, Alexander J., author; Bell, Michael M., advisor; Barnes, Elizabeth A., committee member; Rasmussen, Kristen L., committee member; Davenport, Frances V., committee memberThe internal vortex structure of a tropical cyclone (TC) influences intensity change. Beneficial structural characteristics that allow TCs to capitalize on favorable environmental conditions are an important determinant as to whether a TC will undergo rapid intensification (RI) or not. Accurately forecasting RI is a significant challenge and past work identified characteristics of radial and azimuthal structure of the tangential winds which favor RI, but vertical structure has received less attention. This dissertation aims to define vertical structure in a consistent manner to improve our understanding of how it influences intensity change in observed and modeled TCs, as well as discern when strong winds are more likely to reach the surface with potential for greater impacts. Part 1 investigates the height of the vortex (HOV) in observed TCs and its potential relationships with intensity and intensification rate. As a TC intensifies, the tangential wind field expands vertically and increases in magnitude. Past work supports the notion that vortex height is important throughout the TC lifecycle. The Tropical Cyclone Radar Archive of Doppler Analyses with Recentering (TC-RADAR) dataset provides kinematic analyses for calculation of HOV in observed TCs. Analyses are azimuthally-averaged with tangential wind values taken along the radius of maximum winds (RMW). A threshold-based technique is used to determine the HOV. A fixed-threshold HOV strongly correlates with current TC intensity. A dynamic HOV (DHOV) metric quantifies vertical decay of the tangential wind normalized to its maximum at lower levels with reduced intensity dependence. DHOV exhibits a statistically significant relationship with TC intensity change with taller vortices favoring intensification. A tall vortex is always present in observed cases meeting a pressure-based RI definition in the following 24-hr period, suggesting DHOV may be useful to intensity prediction. In Part 2, numerical modeling simulations are utilized to discern mechanisms responsible for the observed relationships in Part 1. Vertical wind shear (VWS) can tilt the TC vortex by misaligning the low- and mid-level circulation centers which prevents intensification until realignment occurs. Both observed and simulated TCs with small vortex tilt magnitudes possess DHOV values consistent with those observed prior to RI. In aligned TC intensification, DHOV and intensity have a mutually increasing relationship, indicating the metric provides useful information about vertical structure in both tilted and aligned TCs. Vertical vortex growth during RI is sensitive to internal processes which strengthen the TC warm core in the upper-levels of the troposphere. Comparison of a TC simulated in the presence of a concentrated upper-level jet of VWS to a control simulation in quiescent flow indicates that disruption of intensification in the upper levels limits vortex height and intensity without appreciable low- to mid-level tilt. Part 3 focuses on decay of the TC wind field as it encounters friction near the surface in the planetary boundary layer (PBL). Surface winds are important to operational TC intensity estimation, but direct observations within the PBL are rare. Forecasters use reduction factors formulated with wind ratios (WRs) from winds observed by aircraft in the free troposphere and surface winds. WRs help reduce stronger winds aloft to their expected weaker values at the surface. Asymmetries in the TC wind field such as those induced by storm motion can limit the accuracy of static existing WR values employed in operations. A large training dataset of horizontally co-located wind measurements at flight level and the surface is constructed to train a neural network (NN) to predict WRs. A custom loss function ensures the model prioritizes accurate prediction of the strongest wind observations which are uncommon. The NN can leverage relevant physical relationships from the observational data and predict a surface wind field in real-time for forecasters with greater accuracy than the current operational method, especially in high winds.