Lightning data assimilation with comprehensively nudging water contents at cloud-resolving scale using WRF model

Abstract

A new lightning data assimilation (LDA) scheme comprehensively nudging water contents in the WRF model is developed at cloud-resolving scale, which takes the dynamical and thermodynamic conditions into consideration and nudges the low-level water vapor and graupel mass within the mixed-phase region according to the detected total lightning flash rate and model environments (here named C18). The main nudging functions of the LDA scheme in this work are modified based on the work of Fierro et al. (2012, hereafter F12) and Qie et al. (2014, hereafter Q14). To evaluate the application of LDA in high-impact weather simulations and quantitative precipitation forecasts, the three LDA schemes, including F12, Q14 and C18, are tested and compared for two severe squall line cases occurred over the Beijing metropolitan region (BMR). Benefiting from assimilation of lightning data, the simulated storm structure and surface cold pool are improved and closer to the observations for all the three schemes than the control run without LDA. For the F12 scheme, although the simulated thunderstorms are characterized by wide spread stratiform clouds and relatively weaker cold pool intensity and coverage, the positive impacts on both storm evolution and precipitation endures most prominently. For the Q14 scheme, intense downdrafts lead to the strongest cold pool and earlier dissipation of storms comparing with the observations. For the C18 scheme, increased graupel mass affect the cold-cloud processes leading to an earlier onset of rainfall, and the simulated surface cold pool is in better agreement with the observations. Profiting from more moisture added into the lower layers in C18, the storm develops more intensively toward higher altitude and sustains its development over a longer period after LDA, resulting in the best quantitative precipitation forecasts consequently.