A Framework for the Statistical Analysis of Large Radar and Lightning Datasets: Results from STEPS 2000

Timothy J. Lang Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Steven A. Rutledge Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

A framework for the statistical analysis of large radar and lightning datasets is described and implemented in order to analyze two research questions in atmospheric electricity: storms dominated by positive cloud-to-ground (+CG) lightning and estimating the probability of lightning in convection. The framework—a collection of computer programs running in series—is fully modular, allowing the analysis of a variety of datasets based on a study’s objectives, including radar observations, lightning data, observations of meteorological environments, and other data. The framework has been applied to over 2 months of observations of 28 463 cells. The results suggest that +CG-dominated cells contain midlevel positive charge (−10° to −30°C), in contrast to cells dominated by −CG lightning, which typically had positive charge at upper (near −40°C) and lower levels (0° to −10°C). The +CG cells also were larger and more intense, and were associated with environments that were more convectively favorable—in terms of increased moisture, shear, and especially instability—when compared to −CG cells. The framework was also used to examine the probability of lightning occurrence for a spectrum of radar structures. The existence of 30-dBZ echo above the freezing altitude is a “necessary” condition (in ~90% of cases) for lightning occurrence. A “sufficient” condition (in ~90% of cases) is 40-dBZ echo breaching the freezing altitude. Altitude or volume of 40-dBZ echo was the superior estimator for the occurrence of lightning, while 30 dBZ was better for inferring the lack of lightning.

Corresponding author address: Timothy J. Lang, 1371 Campus Delivery, Fort Collins, CO 80523. E-mail: tlang@atmos.colostate.edu

Abstract

A framework for the statistical analysis of large radar and lightning datasets is described and implemented in order to analyze two research questions in atmospheric electricity: storms dominated by positive cloud-to-ground (+CG) lightning and estimating the probability of lightning in convection. The framework—a collection of computer programs running in series—is fully modular, allowing the analysis of a variety of datasets based on a study’s objectives, including radar observations, lightning data, observations of meteorological environments, and other data. The framework has been applied to over 2 months of observations of 28 463 cells. The results suggest that +CG-dominated cells contain midlevel positive charge (−10° to −30°C), in contrast to cells dominated by −CG lightning, which typically had positive charge at upper (near −40°C) and lower levels (0° to −10°C). The +CG cells also were larger and more intense, and were associated with environments that were more convectively favorable—in terms of increased moisture, shear, and especially instability—when compared to −CG cells. The framework was also used to examine the probability of lightning occurrence for a spectrum of radar structures. The existence of 30-dBZ echo above the freezing altitude is a “necessary” condition (in ~90% of cases) for lightning occurrence. A “sufficient” condition (in ~90% of cases) is 40-dBZ echo breaching the freezing altitude. Altitude or volume of 40-dBZ echo was the superior estimator for the occurrence of lightning, while 30 dBZ was better for inferring the lack of lightning.

Corresponding author address: Timothy J. Lang, 1371 Campus Delivery, Fort Collins, CO 80523. E-mail: tlang@atmos.colostate.edu
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