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

Abstract

AbstractA 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.