This work presents simulation results of the storm observed on the 13–14 July 2016 over the Central region of Russia. The Cumulonimbus cloud (Cb) electrification model coupled with the numerical weather prediction model WRF-ARW were used for this study. The prognostic values of the electric field magnitude were compared with observations. Forecast scores were obtained. The results show that the proposed approach of explicit modelling of the electric field is applicable to short-term forecasting of intense convection and passage tracking of storms. Obtaining varying values of the electric field could help to identify the diversity of hazardous weather phenomena associated with convection.
The main threat to society, industry and the environment is an increase in the frequency and magnitude of extreme weather. These phenomena include hazardous convective weather events – intense thunderstorms, heavy rain, squalls and hail. All these weather events are associated with the formation of mesoscale convective systems (MCSs). However, the specific mechanisms affecting the formation and evolution of convective clouds have been insufficiently studied. One of these mechanisms is the atmospheric electrical process, which makes a significant contribution to the initiation of severe weather. Since there is a lack of observation of the electrical parameters in thunderclouds, an alternative tool for this analysis could be the electrification model. The proposed technique is based on an explicit calculation of the generation and separation of the electric charges in convective clouds. Better understanding of atmospheric electrical processes could improve the severe weather forecast characterized by a small spatio-temporal scale. The main objective of this study is the short-term forecast of the storm observed 13–14 July 2016 over central Russia. It also includes an analysis of the electric field intensity threshold for lightning initiation. The Cb model coupled with the numerical weather prediction model WRF-ARW (Wang et al., 2012) are used for this research.
Passage of MCCs according to Doppler weather radar
maps
The analysed MCS began to form over Belarus and the Smolensk region of Russia at 15:00 UTC 13 July 2016. Passage of the storm over the Moscow region began at 18:30 UTC. It moved from the northwest to the east until 22:00 UTC. The convective area accompanied by severe thunderstorm activity anomalies, hail and intense cumulous precipitation was observed. After 00:00 UTC 14 July 2016 the MCS dissipated over the Vladimir and Nizhny Novgorod regions.
The model describes charge generation and the separation processes in
convective clouds (Gardiner et al., 1985; MacGorman et al., 2001; Mansel et
al., 2005; Ziegler et al., 1991). The charges are moving hydrometeors
(graupels, ice and snow crystals, cloud, and rain droplets). The input
for the Cb model are constants and the meteorological data (air temperature,
wind speed, fractions of liquid and solid cloud particles). The main unit of
charge generation includes equations of non-inductive and inductive schemes.
Non-inductive charging occurs due to collision and rebound among the
graupels, the snow and the ice crystals in the presence of supercooled
water. Eq. (1) (Mansel et al., 2005) is used for calculation:
Inductive charging is caused by hydrometeors polarized with the atmospheric
electric field. Equation (2) of the inductive charging implies the interaction
of graupels and cloud droplets (Zeigler et al., 1991):
The resulting charge is calculated as the sum of non-inductive and inductive
charges (Dovgaluik et al.,2013). Equation (3) is used for the calculation:
Pairwise interaction among other hydrometeors is not considered due to the
small size of the charge generated as a result of their collision (Jennings,
1975). The charge per one collision between particles
The meteorological fields are predicted by WRF-ARW v.3.7.1. The system of
nested domains with a decreasing resolution of 18, 6 and 2 km is applied.
The experiments were carried out for the domain of
Figure 1 shows the weather events (a, c) according to the Doppler weather
radar and the simulated electric field intensity (kV m
The Doppler weather radar data are not public. They are available for researchers of Roshydromet only. Please contact the first author if the data are required.
IMG performed numerical experiments, statistical estimations, and analysis of the results and wrote the paper. MMK carried out numerical experiments and analysis of the results. KGR helped in the formulation of the task, analysis of the results, and writing of the paper.
The authors declare that they have no conflict of interest.
This article is part of the special issue “17th EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017”. It is a result of the EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017, Dublin, Ireland, 4–8 September 2017.
This work was supported by the RFBR (Russian Foundation for Basic Research) under grants mol_a 18-35-00044, A 16-05-00822 and A 16-05-00704. It was also supported by EMS through YSTA. Edited by: Victoria Sinclair Reviewed by: two anonymous referees