Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Quantitative Assessment of Tropical Cylcone Simulation Sensitivity in the Community Atmosphere Model.

This work conducted nearly two thousand idealized AGCM simulations to systematically assess the sensitivities of simulated Tropical cyclone (TC) characteristics to changes in model input and evaluate the performance of three surrogate models for approximating the behavior of numerical models. The TC characteristics are intensity, precipitation rate, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). The National Center for Atmospheric Research (NCAR)/Department of Energy (DOE) Community Atmosphere Model (CAM) version 5.1.1 is adopted. First, the Reed-Jablonowski TC test case was upgraded to a version with background vertical wind shear, in which the well-known shear-induced intensity change and structural asymmetry in tropical cyclones are well captured. Then, a statistical framework, consisting of a combination of Latin Hypercube Sampling (LHS) and surrogate models, is used to investigate the sensitivities of the six simulated TC characteristics to five model initial conditions: initial size and intensity of vortex seed, sea surface temperature, vertical lapse rate and mid-level relative humidity. The surrogate models are shown to successfully reproduce the response of CAM to changes in input conditions, and serve as powerful tools for quantifying numerous model input-output relationships with reduced computational burden. Finally, we examined the impact of parameterized physical processes on TC simulation and quantified the relative importance of 24 physical parameters on the six TC characteristics, respectively. The response function between TC characteristics and the associated most sensitive parameters are characterized. A group of ensemble simulations showed that the interactive effect among physical parameters greatly enlarges the uncertainty of simulated TC precipitation, LWCF, SWCF and IWP. Parameter uncertainty in simulated TC intensity is comparable to uncertainty resulting from changes in model initial conditions and model resolution. The Gaussian Spatial Process Model (GaSP) produced robust fits to CAM model responses in TC intensity, LWCF and SWCF, but experienced some difficulty reproducing TC precipitation rate, LWP and IWP.PhDAtmospheric, Oceanic and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133448/1/hefei_1.pd

Geodatabase-assisted storm surge modeling

Tropical cyclone-generated storm surge frequently causes catastrophic damage in communities along the Gulf of Mexico. The prediction of landfalling or hypothetical storm surge magnitudes in U.S. Gulf Coast regions remains problematic, in part, because of the dearth of historic event parameter data, including accurate records of storm surge magnitude (elevation) at locations along the coast from hurricanes. While detailed historical records exist that describe hurricane tracks, these data have rarely been correlated with the resulting storm surge, limiting our ability to make statistical inferences, which are needed to fully understand the vulnerability of the U.S. Gulf Coast to hurricane-induced storm surge hazards. This dissertation addresses the need for reliable statistical storm surge estimation by proposing a probabilistic geodatabase-assisted methodology to generate a storm surge surface based on hurricane location and intensity parameters on a single desktop computer. The proposed methodology draws from a statistically representative synthetic tropical cyclone dataset to estimate hurricane track patterns and storm surge elevations. The proposed methodology integrates four modules: tropical cyclone genesis, track propagation, storm surge estimation, and a geodatabase. Implementation of the developed methodology will provide a means to study and improve long-term tropical cyclone activity patterns and predictions. Specific contributions are made to the current state of the art through each of the four modules. In the genesis module, improved representative data from historical genesis populations are achieved through implementation of a stratified-Monte-Carlo sampling method to simulate genesis locations for the North Atlantic Basin, avoiding potential non-representative clustering of sampled genesis locations. In the track module, the improved synthetic genesis locations are used as the starting point for a track location and intensity methodology that incorporates storm strength parameters into the synthetic tracks and improves the positional quality of synthetic tracks. In the surge module, high-resolution, computationally intensive storm surge model results are probabilistically integrated in a computationally fast-running platform. In the geodatabase module, historic and synthetic tropical cyclone genesis, track, and surge elevation data are combined for efficient storage and retrieval of storm surge data

Analytic studies of local-severe-storm observables by satellites

Attention is concentrated on the exceptionally violet whirlwind, often characterized by a fairly vertical axis of rotation. For a cylindrical polar coordinate system with axis coincident with the axis of rotation, the secondary flow involves the radial and axial velocity components. The thesis advanced is, first, that a violent whirlwind is characterized by swirl speeds relative to the axis of rotation on the order of 90 m/s, with 100 m/s being close to an upper bound. This estimate is based on interpretation of funnel-cloud shape (which also suggests properties of the radial profile of swirl, as well as the maximum magnitude); an error assessment of the funnel-cloud interpretation procedure is developed. Second, computation of ground-level pressure deficits achievable from typical tornado-spawning ambients by idealized thermohydrostatic processes suggests that a two-cell structure is required to sustain such large speeds

The WWRP Polar Prediction Project (PPP)

Mission statement: “Promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hours to seasonal”. Increased economic, transportation and research activities in polar regions are leading to more demands for sustained and improved availability of predictive weather and climate information to support decision-making. However, partly as a result of a strong emphasis of previous international efforts on lower and middle latitudes, many gaps in weather, sub-seasonal and seasonal forecasting in polar regions hamper reliable decision making in the Arctic, Antarctic and possibly the middle latitudes as well. In order to advance polar prediction capabilities, the WWRP Polar Prediction Project (PPP) has been established as one of three THORPEX (THe Observing System Research and Predictability EXperiment) legacy activities. The aim of PPP, a ten year endeavour (2013-2022), is to promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on hourly to seasonal time scales. In order to achieve its goals, PPP will enhance international and interdisciplinary collaboration through the development of strong linkages with related initiatives; strengthen linkages between academia, research institutions and operational forecasting centres; promote interactions and communication between research and stakeholders; and foster education and outreach. Flagship research activities of PPP include sea ice prediction, polar-lower latitude linkages and the Year of Polar Prediction (YOPP) - an intensive observational, coupled modelling, service-oriented research and educational effort in the period mid-2017 to mid-2019

An Exploration of Tropical Cyclone Simulations in NCAR's Community Atmosphere Model.

Using General Circulation Models (GCMs) for tropical cyclone studies is challenging due to the relatively small size of the storms, the intense convection and a host of scale interactions. However, with the advancement of computer architectures, GCMs are becoming capable of running at high horizontal resolutions with grid spacings of less than 60 km. As a result, high-resolution GCMs are becoming a tool of choice to evaluate tropical cyclones in current and future climate conditions. This raises questions concerning the fidelity of GCMs for tropical cyclone assessments. The physical and dynamical components of GCMs need to be evaluated to assess their reliability for tropical cyclone studies. An idealized tropical cyclone test case for high-resolution GCMs is developed and implemented in aqua-planet mode with constant sea surface temperatures. The initial conditions are based on an analytic initial vortex seed that is in gradient-wind and hydrostatic balance and intensifies over a 10-day period. The influence of the model parameterization package on the development of the tropical cyclone is assessed. In particular, different physics parameterization suites are investigated within the National Center for Atmospheric Research's Community Atmosphere Model CAM, including physics versions 3.1, 4 and 5. The choice of the CAM physics suite has a significant impact on the evolution of the idealized vortex into a tropical cyclone. In addition, a test case of intermediate complexity is introduced. Therein it is suggested that a GCM dynamical core be paired with simple moist physics to test the evolution of the test vortex. This simple-physics configuration includes important driving mechanisms for tropical cyclones, including surface fluxes, boundary layer diffusion and large-scale condensation. The impact of the CAM dynamical core (the resolved fluid flow component) on the tropical cyclone intensity and size is evaluated. In particular, the finite-volume, spectral element, Eulerian spectral transform and semi-Lagrangian spectral transform dynamical cores are utilized. The simple-physics simulations capture the dominant characteristics of tropical cyclones and are compared to the CAM 5 full physics results for each dynamical core. The research isolates the impact of the physical parameterizations, numerical schemes and uncertainties on the evolution of the cyclone in CAM.Ph.D.Atmospheric and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91502/1/kareed_1.pd