Impact of Assimilating FY-4A Lightning Data with a Latent Heat Nudging Method on Short-Term Forecasts of Severe Convective Events in Eastern China

In this study, a latent heat nudging lightning data assimilation (LDA) method independent of the flash rate was developed and tested with data from the Lightning Mapping Imager (LMI) onboard the Feng-Yun-4A (FY-4A) satellite based on the Weather Research and Forecasting (WRF) model. In this LDA method, the positive temperature perturbations at the lightning location are first calculated by the difference between the moist adiabatic temperature of a lifted air parcel and the model temperature. The positive temperature perturbations in the mixed-phase region are then assimilated by a nudging method to adjust the latent heat within the convective system. Meanwhile, the water vapor mixing ratio is adapted to the temperature perturbations accordingly to constrain the relative humidity to remain unchanged. This method considers the physical nature of the convective system, in contrast with other LDA methods that establish an empirical or statistical relationship between the lightning flash rates and model variables.

The impact of this LDA method on short-term (≤6 h) forecasts was evaluated using two severe convective events in eastern China: a multi-region heavy rainfall event and a thunderstorm high-wind event. The results showed that LDA could add thermodynamic information associated with the convective system to the WRF model during the nudging period, leading to a more reasonable storm environment. In the forecast fields, the simulations with LDA produced more realistic convective structures, resulting in an improvement in forecasts of precipitation and high winds.