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Climate and Earth system modelling is the use of mathematical representations of key components and properties of the atmosphere, ocean and biosphere to construct computer models. These models – which can range significantly in their complexity, depending on their intended application – are used to simulate important aspects of the Earth system and indicate how they may change in the future.
Modelling the Ocean Heat-Carbon Nexus in Simple Climate Models results in inconsistencies, which could impact future climate projections and emission-to-concentration translation, according to a modelling analysis.
Shipping fuel regulations in 2020 that reduced sulfur dioxide emissions by 80% led to substantial warming over parts of the oceans, according to simulations with Earth system, machine learning, and energy balance models, suggesting a termination shock after marine cloud geoengineering could be severe.
Almost half of land use and nearly three-quarters of greenhouse gas emissions can be reduced by adopting circularity principles and reducing the ratio of animal-sourced protein to plant-sourced protein from 60:40 to 40:60 in European diets.
Earth system model projections of vegetation–climate feedback frequently depend on inaccurate values of evaporation sensitivity to vegetation changes, potentially resulting in misleading conclusions. A promising avenue involves improving the transpiration partitioning parameterizations and incorporating groundwater connections to refine the modelled sensitivity.
Methane concentrations are rising faster than ever in the atmosphere. Now, a compilation of observations points towards increased methane emissions from Arctic wetlands as being partly responsible.
Large language models can summarize, aggregate, and convey localized climate-related data to people in a cost-effective and expeditious manner. This Comment introduces a simple, proof-of-concept prototype and argues that the approach holds the potential to truly democratize climate information.