Climate change is a major threat already causing system damage to urban and natural
systems, and inducing global economic losses of over $500 billion. These issues may be …

Climate variability and weather phenomena can cause extremes and pose significant risk to
society and ecosystems, making continued advances in our physical understanding of such …

In this study, it was investigated that how machine learning (ML) methods show performance
in different problems having different characteristics. Six ML approaches including Artificial …

We present an overview of recent work on using artificial intelligence (AI)/machine learning
(ML) techniques for forecasting convective weather and its associated hazards, including …

Traditional fully-deterministic algorithms, which rely on physical equations and mathematical
models, are the backbone of many scientific disciplines for decades. These algorithms are …

Previous studies have identified environmental characteristics that skillfully discriminate
between severe and significant-severe weather events, but they have largely been limited …

Weather forecasting requires comprehensive analysis of a variety of meteorological data.
Recent decades have witnessed the advance of weather observation and simulation …

In order to aid feature selection in thunderstorm nowcasting, we present an analysis of the
utility of various sources of data for machine-learning-based nowcasting of hazards related …

The study aims to assess the applicability of the current Meso-NH electrical scheme
(CELLS) in the investigation of forest fire ignition. Therefore, the challenge is to diagnose …

Accurate and timely prediction of lightning occurrences plays a crucial role in safeguarding
human well-being and the global environment. Machine-learning-based models have been …