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Abstract

Hailstones have large damage potential; however, their explicit prediction remains quite challenging. The uncertainty in model's initial condition and microphysics are two of the significant contributors to the challenge. This study therefore aims to investigate the impacts of improved initial condition and microphysics on surface hail size and location prediction for a moderate hailstorm occurred in Beijing on 10 June 2016 using the WRF Model’s 3DVar system and the latest revised MP38 bulk scheme. The role of initial condition on hail prediction is first explored by assimilating high-resolution radar and surface observations. Results indicate that DA significantly improves the FSS score of hail size and location prediction. However, even with more accurate initial condition provided by DA, hail prediction still can be affected by microphysical parameterization processes. Then, the role of microphysics is discussed by comparing MP38 with two earlier schemes. MP38 is a newly revised two-moment hail-aware scheme that predicts graupel number concentration (N_g) and density, such modifications produced a smaller and more realistic forecast of hail size because of improved simulation of mass-weighted mean graupel diameter. However, it will significantly underpredict the hail size with only the revision of N_g. The smaller hail size in MP38 further led to a stronger graupel melting process and cold pool, which inhibited the development of spurious convection at the north and improved hail location prediction.The results of this work shed light on the importance of accurate representation of initial condition and microphysical processes in NWP models for explicit hail prediction.