Prediction of lightning activity using WRF-ELEC model: Impact of initial and boundary conditions

Abstract

The impact of initial conditions in predicting lightning activity using the Weather Research and Forecasting (WRF) with the electrification (ELEC) extra package, known as WRF-ELEC model, has been investigated. The severity, frequency, and some physical and dynamical properties of lightning occurred during 11 years (2004–2014) are considered. Four thundercloud events with distinctive characteristics over the Tehran area were chosen for detailed study. The selection process was made based on the observational data received from the Iranian Meteorological Organization (IRIMO), ground-based lightning data from the World Wide Lightning Location Network (WWLLN) and satellite-based lightning data from the Lightning Imaging Sensor (LIS). The WRF-ELEC simulations initialized with the European Centre for Medium-Range Weather Forecasts-ERA Interim (ECMWF-ERA Interim), National Centers for Environmental Prediction Final Analysis (NCEP-FNL) and the NCEP operational Global Forecast System (GFS) data have been conducted to obtain the Number Of Lightning flash density (NOL) associated with each case study. The numerical simulations are compared qualitatively and quantitatively with the observations. Several statistical metrics are used in order to determine the performance of the WRF-ELEC model initialized by various IBCs (initial and boundary conditions) for lightning prediction purposes. The results show that in the most of the studied cases, there is a good agreement between the simulated time-averaged horizontal patterns of the Lightning Potential Index (LPI) obtained from the ERA-Interim-based experiments and the locations of lightning occurrence of WWLLN data as well as LIS observations. Furthermore, GFS-based simulations have a better quantitative performance in the NOL prediction than FNL and ERA-Interim-based simulations regarding the values of Standard Deviation (SD), and centered Root Mean Square Error (RMSE). The results of further statistical analysis using different metrics reveal that ERA-Interim initialization has the best performance of lightning activity prediction.