Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...

Atmospheric dust plays a dual role in Earth's climate: it reflects some sunlight back into space while also absorbing and retaining the planet's heat like an insulating blanket. But while dust likely ...

The algorithms behind generative AI tools like DallE, when combined with physics-based data, can be used to develop better ways to model the Earth's climate. Computer scientists have now used this ...

Our project is designed to unravel the complexities of climate change impacts within the Neponset River Watershed, employing sophisticated methods tailored specifically to this study domain. Through ...

Timeline of atmospheric CO₂ evolution, faunal turnover, and topographic uplift during the Miocene, providing a contextual framework for interpreting ecological and climate model results. (A) ...

Climate change poses interconnected challenges across water, energy, land, and ecosystem services, demanding integrated approaches that link greenhouse gas ...

Over the past 60 years, scientists have largely succeeded in building a computer model of Earth to see what the future holds. One of the most ambitious projects humankind has ever undertaken has now ...

A new machine-learning weather prediction model called GenCast can outperform the best traditional forecasting systems in at least some situations, according to a paper by Google DeepMind researchers ...

Dramatic droughts linked to the decline of the Classic Maya civilization approximately 800 to 1000 CE may not have required any external trigger, according to a new climate modeling study. Instead, ...

Climate-smart food systems research is rapidly evolving to address global challenges around agricultural emissions, supply chain sustainability, and food ...