An improved lightning flash rate parameterization developed from Colorado DC3 thunderstorm data for use in cloud‐resolving chemical transport models

Abstract

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.

Wet scavenging of soluble gases in DC3 deep convective storms using WRF‐Chem simulations and aircraft observations

“…Toluene mixing ratios of approximately 30 pptv and isoprene of 40 pptv were observed in the PBL, suggesting moderate anthropogenic and low biogenic emissions [ Barth et al , ]. Maximum updraft speeds of 15–40 m s −1 for the northern cell and 5–40 m s −1 for the southern cell were observed by the CSU‐CHILL (S‐band and X‐band) and CSU‐PAWNEE (S‐band) dual‐pol system [ Basarab et al , ]. In Figure , NEXRAD column‐maximum radar reflectivity and a vertical reflectivity cross section at the end of the outflow sampling period show a convective core extending to 15 km asl, with reflectivity in the core attaining 70 dB Z .…”

“…Lightning flashes are associated with graupel mass and thus may indicate the amount of mixed‐phase scavenging. More mixed‐phase scavenging in the Oklahoma storm, with a maximum flash rate of 312 flashes min −1 (K. Cummings et al, in preparation, 2016b), than in the Colorado 22–23 June S storm, with a maximum flash rate of 140.4 flashes min −1 [ Basarab et al , ], may explain the higher CH 3 OOH SE for the Oklahoma storm than the Colorado 22–23 June S storm. However, the Colorado 6 June storm has a substantially lower maximum flash rate of 87.5 flashes min −1 [ Basarab et al , ] yet an equivalent CH 3 OOH SE to the Oklahoma storm.…”

“…More mixed‐phase scavenging in the Oklahoma storm, with a maximum flash rate of 312 flashes min −1 (K. Cummings et al, in preparation, 2016b), than in the Colorado 22–23 June S storm, with a maximum flash rate of 140.4 flashes min −1 [ Basarab et al , ], may explain the higher CH 3 OOH SE for the Oklahoma storm than the Colorado 22–23 June S storm. However, the Colorado 6 June storm has a substantially lower maximum flash rate of 87.5 flashes min −1 [ Basarab et al , ] yet an equivalent CH 3 OOH SE to the Oklahoma storm. The lack of a clear dependence of CH 3 OOH SE on flash rate indicates that other factors, such as the amount of liquid versus mixed‐phase removal, may contribute to the amount of CH 3 OOH scavenging in the Oklahoma and Colorado 6–7 June cases.…”

Examining relationships between cloud‐resolving model parameters and total flash rates to generate lightning density maps

“…So, in many cases, an alternative for estimating lightning activity is based on the use of empirically derived relationships involving cloud dynamical and/or microphysical parameters. Several studies have investigated such relationships based, for instance, on the cloud‐top height (Williams, ; Price and Rind, ; Allen and Pickering, ; Wong et al ), the maximum updraught speed ( w max ; Price and Rind, ; Deierling and Petersen, ), the updraught volume (Deierling and Petersen, ), the precipitation ice mass (Deierling et al ; Latham et al ; Carey et al ), the graupel mass or volume (Wiens et al ; Kuhlman et al ; Deierling et al ; Carey et al ; Basarab et al ) or the total mass flux of hydrometeors (Yair et al ; Lynn et al ).…”

Anvil microphysical signatures associated with lightning-produced NO<sub><i>x</i></sub>

“…By appropriately clustering VHF sources associated with a single flash and attributing detected flashes to individual storms, an estimated flash rate can be determined. In this study, LMA-detected VHF sources were sorted into flashes using an automated density-based clustering algorithm developed by E. Bruning and B. Fuchs (Bruning, 2013) and discussed in more detail by Basarab et al (2015) and Fuchs et al (2015). The algorithm was shown by both studies to produce flash rates in close agreement to a previouslydeveloped LMA flash counting algorithm.…”