A database consisting of approximately 4000 storm observations has been objectively analyzed to determine environmental characteristics that produce high radar reflectivities above the freezing level, large total lightning flash rates on the order of 10 flashes per minute, and anomalous vertical charge structures (most notably, dominant midlevel positive charge). The storm database is drawn from four regions of the United States featuring distinct environments, each with coinciding Lightning Mapping Array (LMA) network data. LMAs are able to infer total lightning flash rates using flash clustering algorithms, such as the one implemented in this study. Results show that anomalous charge structures inferred from LMA data, significant lightning flash rates, and increased radar reflectivities above the freezing level tend to be associated with environments that have high cloud base heights (approximately 3 km above ground level) and large atmospheric instability, quantified by normalized convective available potential energy (NCAPE) near 0.2 m s −2 . Additionally, we infer that aerosols may affect storm intensity. Maximum flash rates were observed in storms with attributed aerosol concentrations near 1000 cm −3 , while total flash rates decrease when aerosol concentrations exceed 1500 cm −3 , consistent with previous studies. However, this effect is more pronounced in regions where the NCAPE and cloud base height are low. The dearth of storms with estimated aerosol concentrations less than 700 cm −3 (approximately 1% of total sample) does not provide a complete depiction of aerosol invigoration.

Understanding drop size distribution (DSD) variability has important implications for remote sensing and numerical modeling applications. Twelve disdrometer datasets across three latitude bands are analyzed in this study, spanning a broad range of precipitation regimes: light rain, orographic, deep convective, organized midlatitude, and tropical oceanic. Principal component analysis (PCA) is used to reveal comprehensive modes of global DSD spatial and temporal variability. Although the locations contain different distributions of individual DSD parameters, all locations are found to have the same modes of variability. Based on PCA, six groups of points with unique DSD characteristics emerge. The physical processes that underpin these groups are revealed through supporting radar observations. Group 1 (group 2) is characterized by high (low) liquid water content (LWC), broad (narrow) distribution widths, and large (small) median drop diameters D0. Radar analysis identifies group 1 (group 2) as convective (stratiform) rainfall. Group 3 is characterized by weak, shallow radar echoes and large concentrations of small drops, indicative of warm rain showers. Group 4 identifies heavy stratiform precipitation. The low latitudes exhibit distinct bimodal distributions of the normalized intercept parameter N w, LWC, and D0 and are found to have a clustering of points (group 5) with high rain rates, large N w, and moderate D0, a signature of robust warm rain processes. A distinct group associated with ice-based convection (group 6) emerges in the midlatitudes. Although all locations exhibit the same covariance of parameters associated with these groups, it is likely that the physical processes responsible for shaping the DSDs vary as a function of location.

Accurate prediction of total lightning flash rate in thunderstorms is important to improve estimates of nitrogen oxides (NOx) produced by lightning (LNOx) from the storm scale to the global scale. In this study, flash rate parameterization schemes from the literature are evaluated against observed total flash rates for a sample of 11 Colorado thunderstorms, including nine storms from the Deep Convective Clouds and Chemistry (DC3) experiment in May‐June 2012. Observed flash rates were determined using an automated algorithm that clusters very high frequency radiation sources emitted by electrical breakdown in clouds and detected by the northern Colorado lightning mapping array. Existing schemes were found to inadequately predict flash rates and were updated based on observed relationships between flash rate and simple storm parameters, yielding significant improvement. The most successful updated scheme predicts flash rate based on the radar‐derived mixed‐phase 35 dBZ echo volume. Parameterizations based on metrics for updraft intensity were also updated but were found to be less reliable predictors of flash rate for this sample of storms. The 35 dBZ volume scheme was tested on a data set containing radar reflectivity volume information for thousands of isolated convective cells in different regions of the U.S. This scheme predicted flash rates to within 5.8% of observed flash rates on average. These results encourage the application of this scheme to larger radar data sets and its possible implementation into cloud‐resolving models.

Approximately 63 million lightning flashes have been identified and analyzed from multiple years of Washington, D. C., northern Alabama, and northeast Colorado lightning mapping array (LMA) data using an open-source flash-clustering algorithm. LMA networks detect radiation produced by lightning breakdown processes, allowing for high-resolution mapping of lightning flashes. Similar to other existing clustering algorithms, the algorithm described herein groups lightning-produced radiation sources by space and time to estimate total flash counts and information about each detected flash. Various flash characteristics and their sensitivity to detection efficiency are investigated to elucidate biases in the algorithm, detail detection efficiencies of various LMAs, and guide future improvements. Furthermore, flash density values in each region are compared to corresponding satellite estimates. While total flash density values produced by the algorithm in Washington, D. C. (~20 flashes km À2 yr À1 ), and Alabama (~35 flashes km À2 yr À1 ) are within 50% of satellite estimates, LMA-based estimates are approximately a factor of 3 larger (50 flashes km À2 yr À1 ) than satellite estimates in northeast Colorado. Accordingly, estimates of the ratio of in-cloud to cloud-to-ground flashes near the LMA network (~20) are approximately a factor of 3 larger than satellite estimates in Colorado. These large differences between estimates may be related to the distinct environment conducive to intense convection, low-altitude flashes, and unique charge structures in northeast Colorado. Lightning Mapping Array Detection of LightningThe advent of LMA networks has provided unprecedented detail of lightning channels on the substorm scale. LMAs use time-of-arrival (TOA) techniques from multiple stations to detect the time and location of FUCHS ET AL.LMA FLASH CLIMATOLOGIES 8625 (2016), Climatological analyses of LMA data with an open-source lightning flash-clustering algorithm, J. Geophys.

Abstract. This study examines the occurrence and morphology of frozen-drop aggregates in thunderstorm anvils from the United States Midwest and describes the environmental conditions where they are found. In situ airborne data collected in anvils using several particle imaging and sizing probes and bulk total water instrumentation during the 2012 Deep Convective Clouds and Chemistry experiment are examined for the presence of frozen-drop aggregates. Chains of frozen drops have been only rarely reported before and are hypothesized to aggregate due to electrical forces in the clouds. They were identified in nine of the anvil cases examined to date, suggesting that they are common features in these Midwestern anvils. High concentrations of individual frozen droplets occurred on the tops and edges of one particular set of anvils, while regions closer to the center and bottom of these anvils exhibited fewer frozen drops and more frozen-drop aggregates. Bulk ice water content measurements across these anvils could only be explained by contributions from both small particles (frozen droplets) and large particles (large aggregates of frozen droplets). Dual Doppler radar analysis confirmed the presence of deep and strong (> 15 m s −1 ) updrafts in the parent cloud of one of the anvils. These features contrast with previous anvil measurements in tropical/maritime anvils that evidently do not exhibit the same frequency of frozen-drop aggregates.