An Explicit Charging Scheme for Spectral (Bin) Microphysics (SBM): A WRF-SBM Simulation of a U.S. Continental Squall Line

Abstract An explicit charging scheme was added to the WRF spectral (bin) microphysics (SBM) scheme and compared with the well-tested NSSL bulk microphysics/electrification scheme. The overall approach is a hybrid one because bin-by-bin charges are integrated over the volume of each grid point and then coupled with the electric field generator and discharge scheme within the WRF-ELEC Model. The explicit charging and coupled model were used to simulate a previously studied U.S. continental squall line. Including inductive charging in addition to noninductive charging led to an increase in the relative number of positive discharges compared to negative discharges. Different aerosol concentrations were tested to assess charging sensitivity to aerosol type and size distribution. More lightning events were produced when aerosols were continental, while far less were produced with a simulation with maritime aerosols. SBM simulations produced more cloud-to-ground lightning than the NSSL bulk microphysical scheme, but the number of cloud-to-ground simulated events in both the SBM and NSSL simulations was much smaller than in observations. An SBM sensitivity test with “relaxed” charging constraints produced a greater number of cloud-to-ground events, closer to observed values. The general agreement between the SBM and NSSL in charge structure and lightning production suggests a similarly complete implementation of charge processes. Newly implemented features for both schemes are the calculation of energy discharged per lightning event and the subdivision of the time step for the sedimentation process to prevent the development of excessive electric field magnitudes on large dynamic time steps. Significance Statement This study advances weather research and forecasting by integrating a detailed cloud electrification mechanism into a widely used weather model. It reveals how different charging processes and aerosol pollution influence lightning intensity, frequency, and discharge energy, highlighting the role of air quality in storm electrification. The new model improves predictions of lightning patterns by considering the behavior of cloud-ice particles and their fall speeds, while more frequent calculations of lightning discharges prevent the development of excessive electric fields. Although, in this initial test, it underestimates cloud-to-ground lightning compared to observations, the model aligns well with the standard approach, suggesting consistent treatment of charge processes. These findings deepen our understanding of storm electrification and emphasize the need for further refinement to enhance lightning forecasting accuracy.