In this work, we compare the values of 15 convective indices obtained from radiosonde and microwave temperature and water vapor profiles simultaneously measured over Nizhny Novgorod (56.2°N, 44°E) during 5 convective seasons of 2014–2018. A good or moderate correlation (with coefficients of ~0.7–0.85) is found for most indices. We assess the thunderstorm prediction skills with a lead time of 12 h for each radiosonde and microwave index. It is revealed that the effectiveness of thunderstorm prediction by microwave indices is much better than by radiosonde ones. Moreover, a good correlation between radiosonde and microwave values of a certain index does not necessarily correspond to similar prediction skills. Eight indices (Showalter Index, Maximum Unstable Convective Available Potential Energy (CAPE), Total Totals index, TQ index, Jefferson Index, S index, K index, and Thompson index) are regarded to be the best predictors from both the true skill statistics (TSS) maximum and Heidke skill score (HSS) maximum points of view. In the case of radiosonde data, the best indices are the Jefferson Index, K index, S index, and Thompson index. Only TSS and HSS maxima for these indices are close to the microwave ones, whereas the prediction skills of other radiosonde indices are essentially worse than in the case of microwave data. The analysis suggests that the main possible reason of this discrepancy is an unexpectedly low quality of radiosonde data.

We propose the test-structure method for modeling of electric-field pulsations in the atmosphere. Numerical calculations necessary for interpretation of the behavior of experimental spectra and structure functions of the electric field are performed. Analysis of experimental data shows that the aeroelectric-field strength, being a nonlocal quantity, is formed by an inhomogeneous distribution of space charges surrounding the observation point. Quantitative assessments of the state of the atmospheric boundary layer, electro-gas-dynamic turbulence and convection parameters are discussed on the basis of spectral and structure functions of the electric field.

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Complex field experiments have been undertaken on the basis of the observational set-up arranged in the Upper-Volga Region during the convective seasons of 2005-2010. Spectral and statistical characteristics of electric field perturbations in the vicinity of thunderstorm clouds have been investigated. Statistical analysis allowed us to relate found peculiarities with different stages of thunderstorm generator dynamics. We develop our fractal simulation code to take into account the spatio-temporal dynamics of a cloud discharge, to compare the results with the observations and to address several actual problems of lightning initiation physics.

The El Niño-Southern Oscillation (ENSO) is one of the most conspicuous modes of climate variability (e.g., McPhaden et al., 2020). After the seasonal cycle of summer and winter, the ENSO is the largest cause of climate variations on Earth. The ENSO cycle is made up of warm (El Niño) and cold (La Niña) phases, which replace each other at irregular intervals. During El Niños and La Niñas, the central and eastern equatorial Pacific Ocean heats or cools by a few degrees for 12-18 months, which has major impacts on global temperature (Tsonis et al., 2005) and rainfall (Villafuerte & Matsumoto, 2015) patterns, agriculture and economic output (Adams et al., 1999), and even public health (Kovats et al., 2003).ENSO events are characterized by notable shifts in atmospheric convection patterns, affecting both the north-south Hadley circulation and the east-west Walker circulation. Considering that tropical deep convection is associated with thunderstorms and lightning, it should not be surprising that the ENSO also influences the Earth's electrical environment. However, while the effect of ENSO on lightning has been widely discussed in the literature (