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Louis J. Wicker

Researcher at National Oceanic and Atmospheric Administration

Publications -  84
Citations -  5565

Louis J. Wicker is an academic researcher from National Oceanic and Atmospheric Administration. The author has contributed to research in topics: Supercell & Tornado. The author has an hindex of 34, co-authored 78 publications receiving 4901 citations. Previous affiliations of Louis J. Wicker include University of Georgia & University of Illinois at Urbana–Champaign.

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Time-Splitting Methods for Elastic Models Using Forward Time Schemes

TL;DR: Based on both linear and nonlinear tests, the third-order Runge‐Kutta-based time-splitting scheme appears to offer the best combination of efficiency and simplicity for integrating compressible nonhydrostatic atmospheric models.
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Convective-scale warn-on-forecast system: A vision for 2020

TL;DR: In this article, the authors proposed a new warning paradigm in which numerical model forecasts play a larger role in convective-scale warnings, shifting the warning process from warn on detection to warn on forecast, which has the potential to dramatically increase warning lead times.
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Wind and Temperature Retrievals in the 17 May 1981 Arcadia, Oklahoma, Supercell: Ensemble Kalman Filter Experiments

TL;DR: In this paper, the feasibility of using an ensemble Kalman filter (EnKF) to retrieve the wind and temperature fields in an isolated convective storm has been tested by applying the technique to observations of the 17 May 1981 Arcadia, Oklahoma, tornadic supercell.
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Simulation and Analysis of Tornado Development and Decay within a Three-Dimensional Supercell Thunderstorm

TL;DR: In this article, a three-dimensional numerical simulation using a two-way interactive nested grid is used to study tornado-genesis within a supercell during a 40-minute period, two tornadoes grow and decay within the storm's mesocyclone.
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Ensemble Kalman Filter Assimilation of Radar Observations of the 8 May 2003 Oklahoma City Supercell: Influences of Reflectivity Observations on Storm-Scale Analyses

TL;DR: In this article, a 50-member ensemble was produced by randomly perturbing base-state wind profiles and by regularly adding random local perturbations to the horizontal wind, temperature, and water vapor fields in and near observed precipitation.