Despite continuous improvements, precipitation forecasts are still not as accurate and
reliable as those of other meteorological variables. A major contributing factor to this is that …

Precipitation nowcasting, the high-resolution forecasting of precipitation in a short term, is
essential in various applications in the real world. Previous deep learning methods use …

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 …

Precipitation nowcasting is an important task, which can be used in numerous applications.
The key challenge of the task lies in radar echo map prediction. Previous studies leverage …

Accurate and timely nowcasting precipitation has huge social and economic benefits.
However, the changes in clouds including expansion, dissipation, and distortion are …

Radar echo extrapolation is a basic but essential task in meteorological services. It could
provide radar echo prediction results with high spatiotemporal resolution in a …

Short-range forecasts (nowcasts) of rainfall facilitate providing early warning of severe
rainfall and flooding, which is particularly important in densely populated urban areas …

Forecasting heavy precipitation accurately is a challenging task for most deep learning (DL)-
based models. To address this, we present a novel DL architecture called “multi-scale …

Delivering reliable nowcasts (short-range forecasts) of severe rainfall and the resulting flash
floods is important in densely populated urban areas. The conventional method is advection …