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Patrick Skinner

Research Scientist

University of Oklahoma

United States

Research Interests

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Patrick Skinner is an Adjunct Assistant Professor at the University of Oklahoma, USA. His research primarily focuses on machine learning applications in severe weather prediction, with recent publications addressing topics such as forecasting systems and the impact of biased target variables on model performance. He contributes to advancing methodologies in the Warn-on-Forecast system and evaluating storm-scale probabilistic guidance.

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Collaborators (3)

David Schvartzman

Assistant Professor

University of Oklahoma

UNITED STATES

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Thea Sandmael

University of Oklahoma

UNITED STATES

View details

Matthew Brown

Assistant Professor

University of North Dakota (UND)

UNITED STATES

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Patrick Skinner

Research Interests

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About

Articles (25)

Forecasting Quasi-Linear Convective System Tornado Potential using the Warn-on-Forecast System (WoFS)

Assessing the Impact of Biased Target Variables on Machine Learning Models of Severe Hail

Evaluation of 0–6-Hour Forecasts from the Experimental Warn-on-Forecast System and the Hybrid Analysis and Forecast System for Real-Time Cases in 2021

Limitations of Short-Term Thunderstorm Forecasts from Convection-Allowing Models with 3-km Horizontal Grid Spacing

Retrieval and Quantitative Evaluation of Three-Dimensional Winds in Severe Convection with Multistatic Radar

Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction

Comparing Short-Term Thunderstorm Forecasts from the Warn-on-Forecast System (WoFS) and High-Resolution Rapid Refresh (HRRR)

Storm Displacement Errors in the NSSL Warn-on-Forecast System

A Red Flag Threat Index Based on the Real-Time Mesoscale Analysis for Use in the Warn-on-Forecast System

Advancing Hazardous Weather Prediction in the 2024 NOAA Hazardous Weather Testbed Spring Forecasting Experiment

Using Machine Learning to Predict Convection-Allowing Ensemble Forecast Skill: Evaluation with the NSSL Warn-on-Forecast System

Simulated WSR-88D Observations of the Streamwise Vorticity Current

Collaborative Exploration of Storm-Scale Probabilistic Guidance for NWS Forecast Operations

Verification of Quasi-Linear Convective Systems Predicted by the Warn-on-Forecast System (WoFS)

Warn-on-Forecast System: From Vision to Reality

Quantification of NSSL Warn-on-Forecast System Accuracy by Storm Age Using Object-Based Verification

Doppler Lidar and Mobile Radiosonde Observation-Based Evaluation of Warn-on-Forecast System Predicted Near-Supercell Environments during TORUS 2019

An Iterative Storm Segmentation and Classification Algorithm for Convection-Allowing Models and Gridded Radar Analyses

Improving Estimates of U.S. Tornado Frequency by Accounting for Unreported and Underrated Tornadoes

Short-Term Prediction of a Nocturnal Significant Tornado Outbreak Using a Convection-Allowing Ensemble

Exploring the Watch-to-Warning Space: Experimental Outlook Performance during the 2019 Spring Forecasting Experiment in NOAA’s Hazardous Weather Testbed

Object-Based Verification of GSI EnKF and Hybrid En3DVar Radar Data Assimilation and Convection-Allowing Forecasts within a Warn-on-Forecast Framework

The Second Real-Time, Virtual Spring Forecasting Experiment to Advance Severe Weather Prediction

Exploring the Usefulness of Downscaling Free Forecasts from the Warn-on-Forecast System

Evaluation of an experimental <scp>Warn‐on‐Forecast 3DVAR</scp> analysis and forecast system on quasi‐real‐time short‐term forecasts of high‐impact weather events

Collaborators (3)

David Schvartzman

Thea Sandmael

Matthew Brown

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