This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …

With the rapid development of artificial intelligence, machine learning is gradually becoming
popular for predictions in all walks of life. In meteorology, it is gradually competing with …

WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …

Weather forecasting is a fundamental problem for anticipating and mitigating the impacts of
climate change. Recently, data-driven approaches for weather forecasting based on deep …

We discuss the emerging advances and opportunities at the intersection of machine
learning (ML) and climate physics, highlighting the use of ML techniques, including …

Extreme events such as heat waves and cold spells, droughts, heavy rain, and storms are
particularly challenging to predict accurately due to their rarity and chaotic nature, and …

Foundation models have enormous potential in advancing Earth and climate sciences,
however, current approaches may not be optimal as they focus on a few basic features of a …

Advanced machine learning models have recently achieved high predictive accuracy for
weather and climate prediction. However, these complex models often lack inherent …

Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand
scientific challenge. Recently, machine learning-based weather forecasting models …

As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric
sciences is increasingly adopting data-driven models, powered by progressive …