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 …

It is a critical need to provide timely and valuable alerts of rainstorms and floods to the
public. However, it still remains a world-class challenge to achieve serviceable nowcasting …

Nowadays, both predictive and descriptive modelling play a key role in decision-making
processes in almost every branch of activity. In this article we are introducing, a generic …

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 …

In this paper we discuss and address the challenges of predicting extreme atmospheric
events like intense rainfall, hail, and strong winds. These events can cause significant …

Precipitation nowcasting has always been a hot topic in the field of meteorology, its main
task is to forecast the possible future precipitation events of a certain region in the short term …

The precipitation video datasets have distinctive meteorological patterns where a mass of
fluid moves in a particular direction across the entire frames, and each local area of the fluid …

The importance of climate change prediction and risk assessment has significantly
increased in efforts to tackle the worldwide environmental catastrophe. Deep learning, a …