Lightning Potential Index Research Articles

Impact of 1- and 2-moment cloud microphysics and horizontal resolution on lightning Potential Index within COSMO NWP model

Abstract Lightning is considered one of the most severe meteorological hazards. Currently, many Numerical Weather Prediction (NWP) models make operational use of the Lightning Potential Index (LPI), which enables one to determine areas prone to lightning. In this study, we investigated the ability of LPI to forecast lightning by comparing forecasts of LPI among four configurations of the COSMO NWP model. The four configurations of the COSMO NWP model differ in horizontal resolution (1.2 and 2.2 km) and cloud microphysical scheme (1- and 2-moment cloud microphysics). We evaluated binary forecasts of LPI for varying lead time (1−10h) against the observed number and peak current of lightning flashes recorded by EUCLID network. The evaluation was performed for eight area sizes (4.8 km × 4.8 km to 240 km × 240 km) around model grid points and for 8 days in 2018 when thunderstorms occurred in Central Europe. To assess the success of lightning prediction, we evaluated LPI forecasts using the Area under the Receiver Operating Characteristic (AROC). Results show that the forecasts almost always outperformed the random forecast (AROC = 0.5). As expected, the prediction was more successful for models having higher resolution and the models comprising 2-moment cloud microphysics. The results of the evaluation of LPI forecasts compared to the number of observed lightning were similar to those compared to the sum of the observed peak current. However, differences in results among the four configurations of the model were larger in the latter case. Based on the performed evaluation, we confirm that LPI is a suitable tool for implicit forecasting of lightning in the COSMO NWP model.

Numerical study of performance of two lightning prediction methods based on: Lightning Potential Index (LPI) and electric POTential difference (POT) over Tehran area

The electric POTential difference (POT) and the Lightning Potential Index (LPI) performance in predicting the lightning activity is investigated and the probable relationship between them is examined. These two indices have a similar dependency on microphysical variables such as ice, graupel mixing ratios, and also updraft characteristics within the cloud. Regardless of this similarity, the LPI directly calculated from WRF model is a more favorable parameter for predicting the lightning events in comparison with the POT, which requires an extra package (ELEC) model. Ten years' available data over the Tehran area were reviewed and four thundercloud cases with distinct characteristics (CAPE, time-frequency, intensity) were selected. In order to acquire the associated physical properties, four simulations have been done using the WRF-ELEC model, which is initialized with ERA-Interim data.The assessment conducted within both quantitative and qualitative themes to verify the potential probability of predicting lightning events. In qualitative evaluation framework, the horizontal distribution of LPI and POT were compared to the locations of lightning occurrence detected by WWLLN (The World Wide Lightning Location Network) data as well as the total lightning data obtained from LIS (Lightning Imaging Sensor) in the innermost simulation domain. This evaluation shows that the horizontal patterns of LPI and POT are well consistent with the locations of lightning occurrence. Moreover, in accordance with acquired values of correlation coefficients, it could be inferred that LPI has a better performance in the Number Of Lightning flashes (NOL) prediction than POT. Statistical review of our simulated data (LPI and POT) is performed to study the variation of LPI and POT which resulted in a good correlation between them and therefore, any information about lightning event using LPI values with less computational cost is preferable in the considered domain. Another comparison was carried out based on the calculated correlation coefficient between the simulated NOL and the NOL recorded by WWLLN that does not show any significant correlation between them for none of the cases. Since WWLLN has no observatory in the studied area, inconsistency of the simulated NOL with real atmosphere is justifiable.

Lightning Potential Index performances in multimicrophysical cloud‐resolving simulations of a back‐building mesoscale convective system: The Genoa 2014 event

AbstractSevere weather events are responsible for hundreds of fatalities and millions of euros of damage every year on the Mediterranean basin. Lightning activity is a characteristic phenomenon of severe weather and often accompanies torrential rainfall, which, under certain conditions like terrain type, slope, drainage, and soil saturation, may turn into flash flood. Building on the existing relationship between significant lightning activity and deep convection and precipitation, the performance of the Lightning Potential Index, as a measure of the potential for charge generation and separation that leads to lightning occurrence in clouds, is here evaluated for the V‐shape back‐building Mesoscale Convective System which hit Genoa city (Italy) in 2014. An ensemble of Weather Research and Forecasting simulations at cloud‐permitting grid spacing (1 km) with different microphysical parameterizations is performed and compared to the available observational radar and lightning data. The results allow gaining a deeper understanding of the role of lightning phenomena in the predictability of V‐shape back‐building Mesoscale Convective Systems often producing flash flood over western Mediterranean complex topography areas. Moreover, they support the relevance of accurate lightning forecasting for the predictive ability of these severe events.

Numerical modeling of an intense precipitation event and its associated lightning activity over northern Greece

This study investigates an intense precipitation event and its lightning activity that affected northern Greece and primarily Thessaloniki on 15 July 2014. The precipitation measurement of 98.5mm in 15h at the Aristotle University of Thessaloniki set a new absolute record maximum. The thermodynamic analysis indicated that the event took place in an environment that could support deep thunderstorm activity. The development of this intense event was associated with significant low-level convergence and upper-level divergence even before its triggering and a positive vertical gradient of relative vorticity advection. The high resolution (1.667km×1.667km) non-hydrostatic WRF-ARW numerical weather prediction model was used to simulate this intense precipitation event, while the Lightning Potential Index was utilized to calculate the potential for lightning activity. Sensitivity experiments suggested that although the strong synoptic forcing assumed primary role in the occurrence of intense precipitation and lightning activity, their spatiotemporal variability was affected by topography. The application of the very fine resolution topography of NASA Shuttle Radar Topographic Mission improved the simulated precipitation and the calculated lightning potential.

Calculation of the Lightning Potential Index and electric field in numerical weather prediction models

Modern methods for predicting thunderstorms and lightnings with the use of high-resolution numerical models are considered. An analysis of the Lightning Potential Index (LPI) is performed for various microphysics parameterizations with the use of the Weather Research and Forecasting (WRF) model. The maximum index values are shown to depend significantly on the type of parameterization. This makes it impossible to specify a single threshold LPI for various parameterizations as a criterion for the occurrence of lightning flashes. The topographic LPI maps underestimate the sizes of regions of likely thunderstorm-hazard events. Calculating the electric field under the assumption that ice and graupel are the main charge carriers is considered a new algorithm of lightning prediction. The model shows that the potential difference (between the ground and cloud layer at a given altitude) sufficient to generate a discharge is retained in a larger region than is predicted by the LPI. The main features of the spatial distribution of the electric field and potential agree with observed data.

Calculation of the Lightning Potential Index and Electric Field in Numerical Weather Prediction Models

Calculation of the Lightning Potential Index and Electric Field in Numerical Weather Prediction Models

Long-term impacts of aerosols on precipitation and lightning over the Pearl River Delta megacity area in China

Abstract. Seven-year measurements of precipitation, lightning flashes, and visibility from 2000 to 2006 have been analyzed in the Pearl River Delta (PRD) region, China, with a focus on the Guangzhou megacity area. Statistical analysis shows that the occurrence of heavy rainfall (>25 mm per day) and frequency of lightning strikes are reversely correlated to visibility during this period. To elucidate the effects of aerosols on cloud processes, precipitation, and lightning activity, a cloud resolving – Weather Research and Forecasting (CR-WRF) model with a two-moment bulk microphysical scheme is employed to simulate a mesoscale convective system occurring on 28 Match 2009 in the Guangzhou megacity area. The model predicted evolutions of composite radar reflectivity and accumulated precipitation are in agreement with measurements from S-band weather radars and automatic gauge stations. The calculated lightning potential index (LPI) exhibits temporal and spatial consistence with lightning flashes recorded by a local lightning detection network. Sensitivity experiments have been performed to reflect aerosol conditions representative of polluted and clean cases. The simulations suggest that precipitation and LPI are enhanced by about 16% and 50%, respectively, under the polluted aerosol condition. Our results suggest that elevated aerosol loading suppresses light and moderate precipitation (less than 25 mm per day), but enhances heavy precipitation. The responses of hydrometeors and latent heat release to different aerosol loadings reveal the physical mechanism for the precipitation and lightning enhancement in the Guangzhou megacity area, showing more efficient mixed phase processes and intensified convection under the polluted aerosol condition.

Predicting the potential for lightning activity in Mediterranean storms based on the Weather Research and Forecasting (WRF) model dynamic and microphysical fields

A new parameter is introduced: the lightning potential index (LPI), which is a measure of the potential for charge generation and separation that leads to lightning flashes in convective thunderstorms. The LPI is calculated within the charge separation region of clouds between 0°C and −20°C, where the noninductive mechanism involving collisions of ice and graupel particles in the presence of supercooled water is most effective. As shown in several case studies using the Weather Research and Forecasting (WRF) model with explicit microphysics, the LPI is highly correlated with observed lightning. It is suggested that the LPI may be a useful parameter for predicting lightning as well as a tool for improving weather forecasting of convective storms and heavy rainfall.

Prediction of lightning flash density with the WRF model

Abstract. The Lightning Potential Index (LPI) is a measure of the potential for charge generation and separation that leads to lightning flashes in convective thunderstorms. It is calculated from model simulated updraft and microphysical fields. It was designed to predict the potential of lightning occurrence in operational weather forecasting models, but could possibly be used to improve short-range forecasts of heavy rain. The index is modified here to be model grid-scale transparent between 1 and 4 km (the approximate upper limit of explicit microphysical weather forecasts). Two case studies show that the modification appears to work quite well, and that LPI can be calculated on both an extremely high resolution research-grid (i.e., 1.33 km) and high resolution (i.e., 4 km) operationally compatible forecast grid. Analytical expressions are presented to use the LPI to predict the hourly lightning flash density.