Accurate and timely short-term forecasting services of precipitation variable are significant
for people's lives and property security. The data-driven approaches demonstrate promising …

In recent years, the number of weather-related disasters significantly increases across the
world. As a typical example, short-range extreme precipitation can cause severe flooding …

Nowcasts (ie, short-term forecasts from 5 min to 6 h) of heavy rainfall are important for
applications such as flash flood predictions. However, current precipitation nowcasting …

Currently, most deep learning (DL)-based models for precipitation forecasting face two
conspicuous issues: the smoothing effect in the precipitation field and the degenerate effect …

Accurate and timely rainfall nowcasting is important for protecting the public from heavy
rainfall-induced disasters. In recent years, deep-learning models have been demonstrated …

Radar echo extrapolation has been widely developed in previous studies for precipitation
and storm nowcasting. However, most studies have focused on two-dimensional radar …

Rainfall nowcasting is critical for timely weather predictions and emergency responses,
particularly in flood-prone areas. Existing models, while accurate, often require substantial …

Precipitation nowcasting is an important tool for nowcasting weather. In recent years,
progress has been achieved in some models based on deep learning for precipitation …

Nowadays deep learning-based weather radar echo extrapolation methods have
competently improved nowcasting quality. Current pure convolutional or convolutional …

This short-term weather forecast is particularly important for human production activities and
safety. However, the existing short-term weather forecasts are often difficult to meet the …