Thunderstorm electrification has been studied for hundreds of years. Several mechanisms have been proposed to elucidate the electrification, including convective charging, inductive precipitation charging, and ice crystal-graupel collision charging. Field observations and model studies have demonstrated the vital roles that graupel and ice crystals play in the electrification, but the mechanism of the collision charging is still unclear. The fundamental essence of relative growth rate theory used for explaining the tripole charge structure in thunderclouds also needs a further exploration. We analyze the processes of ice crystal-graupel collision charging from charge migration inside hydrometeors to charge separation between two hydrometeors. The driving effects of temperature gradient and chemical potential gradient in charge migration are clarified, as well as the applicability of the relative growth rate theory, thermoelectric effect and surface tension gradient in different humidities. Based on the understanding from these electrification mechanisms, we propose that the essence of charge separation is driven by non-thermal equilibrium, and future studies on thunderstorm electrification should focus on the dynamical non-thermal equilibrium of cloud particles.

This study investigates the ionospheric variations resulting from thunderstorms that occurred between 00:00 UTC and 08:00 UTC on November 10, 2018, in the central region of Argentina, site of the RELAMPAGO-CACTI Project (Remote sensing of Electrification, Lightning, and Mesoscale/microscale Processes with Adaptive Ground Observations; Clouds, Aerosols, and Complex Terrain Interactions). The data used were the Total Electron Content (TEC), which was computed from Global Navigation Satellite System (GNSS) measurements provided by the Argentinian Continuous Satellite Monitoring Network (RAMSAC by its Spanish acronym) stations and the atmospheric electrical activity data that were provided by the Earth Networks Total Lightning Network (ENTLN). We observed that the generated disturbances have periods less than or equal to 100 minutes and peak-to-peak DVTEC amplitude values reaching up to 1.35 TECU (1 Total electron content unit =1016electrons/m2). We also noted that these atmospheric gravity waves, which show the highest peak-to-peak amplitudes, occur during periods of intense lightning activity. Finally, we found that for a day with Atmospheric Electrical Activity (AEA), the peak-to-peak amplitudes of the waves are approximately 2.91 times greater than the peak-to-peak amplitudes of a day without AEA.

Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF (and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.

The development of extremely powerful thunderstorm which took place on August 19, 2015 is discussed in this paper. High depth hail cloud originated on the Black Sea Coast and classified as a supercell as well as several weaker hailstorms passed more than 1000 km over Northern Caucasus of Russia, the Caspian Sea, and then invaded the territory of Kazakhstan. During more than 20 hours of existence this supercell produced heavy hail, rain, intense lightning discharges, gust and tornado which rarely occurs in the region. The study of the structure and characteristics of the thunderstorm during the formation of electrical discharges and their frequency were of particular interest. According to the forecast, development of convective clouds and separate thunderstorms were expected, though the powerful hail process was not expected due to small vertical temperature gradients and the absence of cold fronts. Supercell was tracked by 5 radars located in this area, which showed its right-hand development with clock-wise deviation from the leading stream on 40-50 degrees to the right and the resulting speed of propagation was about 60-85km/h. The maximum reflectivity factor exceeded value 75dBZ, top of the clouds reached 15-16km and the height of the hail core raised on 11.2km. The size of hailstones size on most of the hail path was 2–3cm, and at the peak of cloud development - 4–5cm. Maximum frequencies of cloud-to-ground flashes of negative and positive polarities reached 30-35min-1 and 60-70min-1 correspondingly, while frequency of cloud-to-cloud flashes was significantly higher and amounted up to 300-500min-1 at the peak of the supercell development. An important fact is that the maximum frequency of flashes of different types coincided in time, showing that the reason of all discharges is similar. Total current of the cloud-to-ground flashes of positive and negative polarities was almost identical in magnitude and differed by sign. It was 200-300 kiloampere at the peak of thunderstorm development. The minimum value of radiation temperature, measured by SEVIRI radiometer installed onboard of Meteosat-10 satellite in 10.8 μm channel, was near to -60ºC. The minimum temperature value on the top of the supercell was comparable to coupled radar and sounding data. The most intensive precipitation flux derived from radiometric measurements was about 22000m3/sec; at the same period radars assessments showed precipitation up to 550mm/h (mixed phase precipitation) and size of hail 4.5cm. The combined satellite-radar-lightning data analysis showed that radar derived characteristics of the supercell reached their maximums earlier than maximum in lightning activity. The highest correlation coefficient between radar and lightning characteristics of the supercell storm was found for pair maximum reflectivity and intensity of LF (0.55) and VHF (0.66) discharges. Estimations of relationship between hail size and lightning activity showed that with increasing hail size, thunderstorm activity increases for both cloud-to-ground and intracloud flashes (on the level 0.46 - 0.59). Analysis of doppler-polarimetric data showed strong inflow zone associated with tornado. Tornadic debris signature was manifested by radar reflectivity factor ZH > 60 dBZ, differential reflectivity ZDR > -1 dB, copolar cross-correlation coefficient ρHV < 0.6, and it was collocated with the tornado vortex signature. Doppler velocities in mesocyclone zone reached values -43 and +63 m/s. Prominent radar echo hook was identified in 1.5 km layer above the ground, while ZDR columns was relatively narrow (4–8 km wide) and not very deep (4.5 km).

We use the third version of the Canadian Local Climate Model as a diagnostic tool to study the climatology of observed CG lightning activity at Maniwaki (latitude: 46,23°N; Longitude: 75,58°W). We examine the dependence between the hourly lightning activity and the related atmospheric variables during the warm season of sixteen years (between 1984 and 2004). The goal of this research is: a) to evaluate the atmospheric static state evolution and its moisture contents for conditions having generated lightning occurrence, b) to develop a CG lightning parameterization, and c) to verify this CG lightning parameterization on other Canadian areas. The freezing level altitude and the precipitable water content are used to estimate the static air instability and its moisture content respectively. These two parameters are served to develop the CG lightning parameterization. A comparison between the observations and simulations CG lightning occurrence and frequency at Maniwaki showed a mean absolute error rate of 27% and 55% respectively. We apply this parameterization at four Canadian regions, distributed from west to east. The simulated CG lightning results are comparable to observed CG lightning at Maniwaki and tested regions. The application of the CG lightning parameterization to the daily data enabled us to find the monthly results. This application represents a preliminary stage for validation this parameterization in regional numerical models in Canada during the historic period.

: This study investigates the use of various thunderstorm indices in predicting severe thunderstorms events during the monsoon season in four different regions in India. The research evaluates the performance of the prediction model using a model skill score and utilizes the Weather Research and Forecasting (WRF) model with the double moment microphysics scheme to simulate model cases. It also compares fifteen thunderstorm indices derived from the ERA5 dataset to identify the most effective index for predicting severe thunderstorms events. The results of this study show that in-corporating thunderstorm indices with model skill scores improves severe thunderstorms fore-casting in the monsoon season in India. The result revealed that determining the optimal threshold for each index is crucial in achieving accurate predictions. The study also highlights the importance of considering multiple indices rather than relying on a single index to predict severe thunderstorms events. The advance indices such as Energy Helicity Index (EHI), Supercell Composite Parameter (SCP), mainly works well with extreme severe thunderstorms. The simplistic indices can predict the weak or severe thunderstorm easily. The use of multiple thunderstorm indices can also help mete-orologists to make more accurate predictions, which can further enhance public safety. In conclu-sion, this study demonstrates the potential of incorporating thunderstorm indices with model skill scores like HSS and TSS and combinations of different skill scores in severe thunderstorms fore-casting during the monsoon season in India. Future research can build upon the findings of this study to develop more accurate and reliable severe weather forecasting models.

Tornadoes remain an active subject of observational and numerical research due to the damage and fatalities they cause worldwide as well as poor understanding of their behavior, such as what processes result in their genesis and what determines their longevity and morphology. A numerical model executed on a supercomputer run at high resolution can serve as a powerful tool for exploring the rapidly evolving tornado-scale features within a simulated storm, but saving large amounts data for meaningful analysis can result in unacceptably slow model performance, an unwieldy amount of saved data, and saved data spread across millions of files. In this paper, a system for efficiently saving and managing hundreds of terabytes of compressed model output is described in order to support a supercomputer simulation of a tornadic supercell thunderstorm. The challenges of managing a simulation spanning over a quarter trillion grid volumes across the Blue Waters supercomputer are also described. The simulated supercell produces a long-track EF5 tornado, and the near-tornado environment is described during tornadogenesis, where single upward-growing vortex undergoes several vortex mergers before transitioning into a multiple vortex tornado.

BKW is a highly efficient Storage Function-type rainfall-runoff model that utilizes the steady-state storage (S) and outflow (Q) of a catchment at different rainfall intensities as the S-Q relation of the catchment. For the inundation nowcasting of urban areas under high-intensity, short-duration rainfall, a Storage Function-type model is a judicious choice. However, S-Q hysteresis exists in the catchment S-Q relation, and BKW is unable to exhibit hysteresis due to assuming that the S-Q relation of a catchment is a nonlinear relation. The S-Q hysteresis can influence the outflow estimation of BKW, reducing the model's accuracy. Through the evaluation of analytical solutions, we found that the change in rainfall intensity dominates the S-Q relation of a catchment. The S-Q relation during a rainfall event is a dynamic process rather than a monotonic nonlinear relation. By applying the dynamic S-Q relation in BKW, we improved BKW to become a highly efficient and accurate rainfall-runoff model for small urban catchments.