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Full-Text Articles in Physical Sciences and Mathematics
An Investigation Of The Conditional Practical Predictability Of The 31 May 2013 Heavy-Rain-Producing Mesoscale Convective System, Aidan Kuroski
An Investigation Of The Conditional Practical Predictability Of The 31 May 2013 Heavy-Rain-Producing Mesoscale Convective System, Aidan Kuroski
Theses and Dissertations
On 31 May 2013, strong thunderstorms initiated in west-central Oklahoma with one of the storms eventually creating a very strong tornado near El Reno, OK. The storms then grew upscale into a quasi-stationary mesoscale convective system that produced prolonged heavy rainfall that led to severe flooding across parts of Oklahoma, including the Oklahoma City metropolitan area. A 50-member ensemble of short range (0-24 h) forecasts was conducting using a set of initial conditions generated via cycled data assimilation to quantify event predictability and identify forecast sensitivities, primarily with CI and initial upscale growth. Both a composite and ensemble sensitivity analysis …
Downstream Predictability Of The Path Of Severe Wind Producing Mcss Using Ruc Analysis Data, Russell Danielson
Downstream Predictability Of The Path Of Severe Wind Producing Mcss Using Ruc Analysis Data, Russell Danielson
Theses and Dissertations
A method for predicting the track of mesoscale convective systems (MCSs) is developed, based upon meteorological parameters in the path of the systems. Rapid Update Cycle model analysis from the years 2007 through 2011 were used to gather meteorological data for 94 MCS events. An artificial neural network model was developed to predict whether the MCS will track to the “Right”, “Left”, or stay on its current path. The most important parameters to predict the track of an MCS in this model are precipitable water, most unstable CAPE, 700hPa temperature, surface-500hPa mean wind, low-level equivalent potential temperature difference, and 700-500hPa …