Editorial Type:
Article
Article Type:
Research Article

Assessing the Predictability of Convection Initiation in the High Plains Using an Object-Based Approach

Brock J. Burghardt Atmospheric Science Group, Department of Mathematical Sciences, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin

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Clark Evans Atmospheric Science Group, Department of Mathematical Sciences, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin

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Paul J. Roebber Atmospheric Science Group, Department of Mathematical Sciences, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin

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Print Publication:
01 Apr 2014
DOI:
https://doi.org/10.1175/WAF-D-13-00089.1
Page(s):
403–418
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Abstract

This study investigates the short-range (0–12 h) predictability of convection initiation (CI) using the Advanced Research Weather Research and Forecasting (WRF) Model (ARW) with a horizontal grid spacing of 429 m. A unique object-based method is used to evaluate model performance for 25 cases of CI across the west-central high plains of the United States from the 2010 convective season. In the aggregate, there exists a high probability of detection but, due to the significant overproduction of CI events by the model, high false alarm and bias ratios that lead to modestly skillful forecasts. Model CI objects that are matched with observed CI objects show, on average, an early bias of about 3 min and distance errors of around 38 km. The operational utility and inherent biases of such high-resolution simulations are discussed.

Current affiliation: Atmospheric Science Group, Department of Geosciences, Texas Tech University, Lubbock, Texas.

Corresponding author address: Dr. Clark Evans, Dept. of Mathematical Sciences, University of Wisconsin–Milwaukee, P.O. Box 413, Milwaukee, WI 53201-0413. E-mail: evans36@uwm.edu

Abstract

This study investigates the short-range (0–12 h) predictability of convection initiation (CI) using the Advanced Research Weather Research and Forecasting (WRF) Model (ARW) with a horizontal grid spacing of 429 m. A unique object-based method is used to evaluate model performance for 25 cases of CI across the west-central high plains of the United States from the 2010 convective season. In the aggregate, there exists a high probability of detection but, due to the significant overproduction of CI events by the model, high false alarm and bias ratios that lead to modestly skillful forecasts. Model CI objects that are matched with observed CI objects show, on average, an early bias of about 3 min and distance errors of around 38 km. The operational utility and inherent biases of such high-resolution simulations are discussed.

Current affiliation: Atmospheric Science Group, Department of Geosciences, Texas Tech University, Lubbock, Texas.

Corresponding author address: Dr. Clark Evans, Dept. of Mathematical Sciences, University of Wisconsin–Milwaukee, P.O. Box 413, Milwaukee, WI 53201-0413. E-mail: evans36@uwm.edu
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