Assessment of the Efﬁcacy of Lightning Forecast Over India: A Diagnostic Study A. SANDEEP, 1,2 A. JAYAKUMAR, 1 M. SATEESH, 1 SAJI MOHANDAS, 1 V. S. PRASAD, 1 and E. N. RAJAGOPAL 1 Abstract—Lightning has emerged as one of the major weather hazards in India. Lightning forecasts are introduced into the operational National Centre for Medium Range Weather Fore- casting regional uniﬁed model (NCUM-R) to predict the events in advance. A new blended electric scheme following McCaul et al. (2009) is employed to predict the lightning ﬂash count as a useful tool for day-to-day prediction of thunderstorm activity and inten- sity. A total of four numerical experiments, namely CNTL, EXP1, EXP2, and EXP3, were conducted by using the NCUM-R based on the graupel water path (GWP) amount and the process allowing the snow-rain collisions to form a graupel. The numerical simulation forecasts are compared with the Indian Air Force and Indian Institute of Tropical Meteorology earth network lightning sensor data. A case study of a convective system associated with a severe lightning event that occurred on 7 February 2019 over the northern region of India is diagnosed. The observations indicate stronger lightning cells present over the Haryana–Punjab region, with a leaf- like extension through south-eastwards and continuing up to the Himalaya foothills. Such south-eastward progression of the light- ning system is well captured in all the experiments. However, when the GWP threshold is set to 200 g m -3 , and allowing for the snow- rain collision process, the counts are improved by approximately 50% compared to the control run, and is closely agree with the observation count. Temporal evolution characteristics of the ver- tical distribution of the hydrometeors and vertical velocity support the formulation of the revised lightning parameterization scheme. Statistical metrics were computed for the pre-monsoon month indicating the robustness of the model with the revised scheme. Hence, the revised scheme is chosen for the operational imple- mentation of the lightning ﬂash prediction system of the NCUM-R. Further modiﬁcations of the electric scheme are warranted based on the cloud microphysics response over different weather regimes. Keywords: Numerical weather prediction/forecasting, fore- cast veriﬁcation, convective storms, lightning, observational data. 1. Introduction Lightning is one of the most lethal natural phe- nomena, causing substantial damage to human life and property, renewable energy production, and electric-power networks (Cooper and Holle 2019). According to the National Disaster Management Authority of India reports from 1967 to 2012, light- ning alone accounted for about 39% of deaths (NDMA 2018). A total of 5259 people died due to lightning strike from 1979 to 2011, with a fatality rate of about 0.24 per million population per year (Singh and Singh 2015). The climatological features of lightning strikes have been studied based on the Tropical Rainfall Measurement Mission satellite dataset, where the monthly and seasonal variations in lightning strikes across different geographical regions of India were discussed (Manohar et al. 1999; Nath et al. 2009; Lal and Pawar 2009; Tinmaker et al. 2010; Kumar and Kamra 2012; Tinmaker and Chate 2013; Murugavel et al. 2014). The extensive hot and humid land region of the inter-tropical convergent zone in eastern India is more likely to lead to the development of high ﬂash rate density (Tinmaker and Chate 2013). A few studies have addressed the spa- tiotemporal variability in lightning ﬂash rates over land regions (Kandalgaonkar et al. 2005; Ranalkar and Chaudhari 2009; Pawar et al. 2012; Choudhury et al. 2016; Saha et al. 2017b). Land–ocean contrasts in the lightning activity in the Arabian Sea and Bay of Bengal were studied by Kandalgaonkar et al. (2010) using satellite-based ﬂash data. Lightning strikes have been found to have good correspondence with aerosol loading, vegetation cover, and convective instability/precipitation, as discussed by Saha et al. (2017b). In recent times, the relationship between lightning ﬂash and the El Nin ˜o Southern Oscillation (ENSO) and various other large-scale modes of 1 National Centre for Medium Range Weather Forecasting (NCMRWF), Project Scientist-D, NCMRWF, MoES, A-50, Insti- tutional Area, Sector-62, Noida, UP 201309, India. E-mail: aravetisandeep@gmail.com 2 School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK. Pure Appl. Geophys. Ó 2020 Springer Nature Switzerland AG https://doi.org/10.1007/s00024-020-02627-5 Pure and Applied Geophysics