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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.
Hueholt et al. find that considering how the rate of temperature change contributes to ecosystem risk helps inform future hypothetical design of climate intervention scenarios
Stronger negative cloud feedback due to a shift from supercooled clouds to warm clouds under climate warming weakens extratropical cloud feedback and impacts climate sensitivity and uncertainty in recent climate models, suggests an analysis of satellite observations and simulations.
Aerosol misrepresentations in many regional climate models largely explain why their simulations underestimate the summer warming in Western Europe in the past 40 years, according to a multi-model analysis.
Stratospheric aerosol injection, marine cloud brightening, and cirrus thinning are less effective in cooling the Arctic than the globe and may lead to increased risk of wildfires and permafrost thawing, according to an analysis of global climate model simulations.
A major part of the increase in Earth’s energy imbalance observed during the period 2001–2019 can be attributed to a reduction in anthropogenic aerosol emissions, according to an analysis of observations of top-of-atmosphere radiative flux and multi-model ensemble simulations.
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.
Climate models have evolved from research tools to underpin decision-making across the globe. To provide optimal value for society in the future, the models need to be made operational.
