Advances in deep learning applications to severe convective weather forecasting: rainstorms, hail, thunderstorm winds and tornadoes
Meng He
Severe convective weather (SCW) forecasting has emerged as a cutting-edge research focus due to its complex dynamical characteristics and significant socioeconomic impacts. However, the advent of deep learning (DL), with its capacity for extracting massive information and modeling non-linear relationships, offers a promising alternative for enhancing the accuracy of SCW forecasts. This study reviews advances in DL applications to SCW forecasting. It begins by summarizing current mainstream DL te