An explicit method of mesoscale convective storm prediction for Central region of Russia Inna M. Gubenko (img0504@yandex.ru) and Konstantin G. Rubinstein Hydrometeorological Research Center of Russia INTRODUCTION This work presents simulation results of convective storm using numerical weather prediction model. Convective event was observed over European part of Russia (Smolensk, Moscow, Vladimir and Nizhny Novgorod region) 13.07.2016 – 14.07.2016. Passage of a convective storm accompanied by a number of dangerous weather events –intensive lightning activity, rain, hail, wind squalls, and tornado caused human injuries, destruction of infrastructure and leaded to serious economic losses (Fig.1). MAIN OBJECTIVE Short-term forecast of convective weather hazards using numerical mesoscale model WRF-ARW (Weather Research and Forecasting) coupled with Cb electrification model. Fig.1. Storm and its consequences in Moscow region, 13-14 of July, 2016 [http://www.metronews.ru/novosti/groza-v-moskve-13-ijulja-2016-pol-zovatelej-seti-pokorili-vspyshki-molnii-v-stolice/Tpopgn---KGtqWpdWJkRZo] CASE STUDY OF INTENSIVE CONVECTION EVENT: BACKGROUND Mesoscale convective complex (MCC) was formatting over border of Belarus and Smolensk region of Russia since 15:00 UTC13.07.2016. According to radar data passage of MCC over Moscow region started at 18:30 UTC and was moving from North-West to East till 22:00 UTC . Example of observational maps are demonstrated at Fig. 2 with convective (severe thunderstorm activity anomalies and hail – Fig.3) and stratiform areas with intensive cumulous precipitation [http://www.meteoinfo.ru/news/1-2009-10-01-09-03-06/12903-14072016-]. After 00:00 UTC 14.07.2016 MCC started to dissipate over Vladimir and Nizhniy Novgorod regions. Fig. 3. Intensive lightning activity areas over Moscow region (21:00 UTC, 13.07.2016). Thunderstorm detectors and synoptic maps [http://www.meteoinfo.ru/news/1-2009-10-01-09-03-06/12903-14072016-]. Fig. 2. Passage of MCC over Moscow region, 13.07.2016. DMRL-S radar maps. CUMULONIMBUS ELECTRIFICATION MODEL DESCRIPTION NUMERICAL MESOSCALE MODEL WRF-ARW WRF model is the atmospheric modeling system designed for meteorological research and numerical weather prediction [http://www2.mmm.ucar.edu/wrf/users/]. Cb electrification model is a set of equations describing the processes of the generation and separation of electric charges in convective clouds, constants and meteorological data (air temperature, wind speed, fractions of liquid and solid cloud particles). Non-inductive charge generation: implies the interaction of solid hydrometeors (ice crystals+graupels, particles of snow+graupels) [Mansel, et al., 2005; MacGorman, et al, 2001; Ziegler et al, 1991, 1986]: WRF-ARW v.3.7.1 configuration: Forecasts from 00-00 UTC 13.07.2016 Domain 896×472 points Horizontal resolution 2 km Vertical levels 30 levels Time step 15 min Time moments 97 moments Microphysics Thompson Cu_microphysics Grell-3 SW and LW- radiation RRTMG Surface and boundary layer Noah Initial and boundary conditions 0.5° GFS where S –non-inductive generation between interacted solid hydrometeors, C/m·s; δq1,2 – charge produced in one collision, C; E1,2 – collision coefficient of hydrometeors; V1,2 – gravitational sedimentation speed of hydrometeors, m/s; D1,2 – diameter of hydrometeors, m. Electric potential (V): Charge per one collision [Mansel, et. al., 2005; MacGorman, et al, 2001; Ziegler et al, 1991,1986]: where φ - electric potential, V; ρt - total space charge density, C/m3; ε0=8,8542·10-12 F/m - electric constant. where V- particle terminal speed, m/s; δL- cloud water content function; f(tau) - temperature function, ºC. Electric field intensity (kV/m): SIMULATION RESULTS Fig. 4 demonstrates forecasting maps of simulated electric field potential difference in a layer of 0-8 km (MV) obtained by WRF-ARW model coupled with Cb electrification model. Areas where electric field potential difference exceed 260 MV indicate on thunderstorm cells. CONCLUSIONS Proposed approach of explicit modeling of the electric field is applicable to short-term forecasting of intense convection and tracking of isolated storms, convective cells and mesoscale convective complexes.   Obtained potential difference values could help to identify the various hazardous weather phenomena associated with convection. 19-00 UTC 19-30 UTC 20-00 UTC 18-30 UTC 20-30 UTC 21-30 UTC 21-00 UTC 22-00 UTC ACKNOWLEDGEMENTS This work was supported by the RFBR (Russian Foundation for Basic Research) under grants А 15-05-02395 and A 16-05-00822. Fig. 4. Simulated electric field potential difference (MV) of MCC. Moscow region, 18:30-22:00 UTC, 13.07.2016