Applying the analogy method to improve the forecasting of strong convection

Strong convective weather, including thunderstorms, severe winds, hail, tornados, and short-term heavy rainfall, is a type of weather phenomenon that is extremely difficult to predict owing to its small spatial scales and short-term duration. In recent years, high-resolution numerical models have become the focus for weather forecasters to predict strong convective weather. They output simulated radar reflectivities and many other physical parameters that directly display the locations of strong convective weather for forecasters. However, these models have errors, which greatly limit their accuracy in convective weather forecasting.

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