A comparison of climate models finds that much of the variation in their predictions of global warming arises from differences in how they simulate the response of convective processes to warming.
Journal of Advances in Modeling Earth Systems (JAMES)
A New Way to Fingerprint Drivers of Water Cycle Change
Simulations of tropical ocean convection help distinguish climate effects resulting from large-scale changes in atmospheric circulation from those resulting from higher temperatures.
Interpreting Neural Networks’ Reasoning
New methods that help researchers understand the decision-making processes of neural networks could make the machine learning tool more applicable for the geosciences.
Pushing the Computational Limits of Climate Simulation
Researchers apply a superparameterization technique to boost the accuracy and efficiency of climate predictions generated by the Energy Exascale Earth System Model.
Soil Moisture Drives Great Plains Cloud Formation
A new study shows that models that reproduce moisture on land are better at accurately recreating cumulus cloud behavior.
A “Super” Solution for Modeling Clouds
Climate models struggle to accurately portray clouds because the models cannot resolve the scales at which clouds form. A new study demonstrates a potential fix for the problem.
One Step Closer to a Milestone in Climate Modeling
A pair of revisions to the Energy Exascale Earth System Model improves its ability to capture late afternoon and nocturnal rainfall as well as the timing and movement of convection.
How Will the Jet Stream Respond to Future Warming?
Simulations that test different approaches to modeling radiation suggest a commonly used scheme fails to fully capture changes in midlatitude circulation associated with climate change.
Improving Estimates of Long-Term Climate Sensitivity
New modeling casts doubt on the suitability of running experiments with fixed sea surface temperatures to understand the effects of cloud aggregation on Earth’s climate.
Capturing the Dynamism of Plant Roots in Models
Simulating the dynamic nature of plant root profiles in Earth system models improves the representation of the carbon and water cycles.
