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Exploring Tornadogenesis with High-Resolution Simulations Initialized with Real Data
(2012)
Despite large advances in our understanding of tornadogenesis over the past fifty years, a comprehensive dynamical understanding of the processes behind tornado formation remains elusive. The purpose of this dissertation ...
Using Deep Learning to Improve Prediction and Understanding of High-impact Weather
(2020-05)
This dissertation describes the application of convolutional neural networks (CNN), a type of deep-learning method, to high-impact weather. CNNs are specially designed to learn directly from spatial grids, which improves ...
DOWNSCALING TECHNIQUES FOR RETRIEVAL OF NEAR-SURFACE METEOROLOGICAL FIELDS AND TURBULENCE PARAMETERS FROM ATMOSPHERIC NUMERICAL MODEL OUTPUTS
(2012)
The Weather Research and Forecasting (WRF) model has evolved toward a self- contained numerical weather prediction system, capable of modeling atmospheric mo- tions ranging from global to microscales. The promise of such ...
Applications of Gaussian Mixture Model to Weather Observations
(2011)
The estimation of weather parameters such as attenuation and rainfall rates from weather radar data has been based mainly on deterministic regression models. The applications of a Bayesian approach to weather parameters ...
Applications of Gaussian Mixture Model to Weather Observations
(2011)
The estimation of weather parameters such as attenuation and rainfall rates from weather radar data has been based mainly on deterministic regression models. The applications of a Bayesian approach to weather parameters ...
APPLICATIONS OF ENSEMBLE KALMAN FILTER DATA ASSIMILATION: FROM CONVECTIVE THUNDERSTORMS TO HURRICANES
(2010)
For the numerical prediction of severe thunderstorm and hurricane, data assimilation is one of the necessary tools to obtain accurate initial conditions. Ensemble Kalman filter (EnKF) is a state of the art data assimilation ...
MATHEMATICAL THEORY IN CLASSIFICATION AND SEGMENTATION
(2012)
We develop several mathematical approaches to solve a series of questions of interdisciplinary research interests. New distance functions are designed for the verification of meteorological forecasts. Modern active contour ...
A method for calibrating probabilistic forecasts
(2013)
One aim of the Warn-on-Forecast initiative is to transform the warning paradigm of rare convective events (RCEs) from warn-on-detection to one where RCE warnings are informed by short-term, high resolution numerical forecasts ...
Sensitivities of Explicit Hail Predictions and Convective Scale Ensemble Forecasting to Microphysics Parameterizations and Ensemble Data Assimilation Configurations
(2020-05)
The explicit prediction of deep, moist convection is challenging because small model and initial condition errors rapidly grow and degrade forecast skill. Microphysics schemes employed by convection-allowing models represent ...