3D anelastic simulations find that both convective zone Busse columns and weather-layer PV homogenization produce Jupiter-like jets, with the weather layer causing deviations in thermal wind balance and long-term high-latitude jet migration.
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Early Venus experienced large seasonal and latitudinal insolation redistribution but only modest orbit-averaged flux changes, making atmospheric opacity the dominant control on surface temperature rather than orbital forcing.
The singular immersion freezing model applies only under limited cooling rates while the time-dependent approach integrates better with particle-based aerosol microphysics.
A flow matching deep learning emulator trained on multiple SSPs generates forced climate responses for unseen scenarios and is validated against the MESMER-M statistical emulator.
ICON and IFS-FESOM capture the global distribution of Köppen-Geiger climate categories but show regional biases dominated by precipitation inaccuracies, and inter-model differences exceed the 30-year climate change signal in many zones.
citing papers explorer
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Superrotation and Jet Migration in Simulations of Jupiter's Convective Zone and Weather Layer
3D anelastic simulations find that both convective zone Busse columns and weather-layer PV homogenization produce Jupiter-like jets, with the weather layer causing deviations in thermal wind balance and long-term high-latitude jet migration.
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Seasonal Insolation Variability on Early Venus: Implications for Energy Budget
Early Venus experienced large seasonal and latitudinal insolation redistribution but only modest orbit-averaged flux changes, making atmospheric opacity the dominant control on surface temperature rather than orbital forcing.
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Immersion freezing in particle-based aerosol-cloud microphysics: a probabilistic perspective on singular and time-dependent models
The singular immersion freezing model applies only under limited cooling rates while the time-dependent approach integrates better with particle-based aerosol microphysics.
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Emulating the Forced Response of Climate Models with Flow Matching
A flow matching deep learning emulator trained on multiple SSPs generates forced climate responses for unseen scenarios and is validated against the MESMER-M statistical emulator.
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Evaluating local climate in global storm-resolving models with the K\"oppen-Geiger classification
ICON and IFS-FESOM capture the global distribution of Köppen-Geiger climate categories but show regional biases dominated by precipitation inaccuracies, and inter-model differences exceed the 30-year climate change signal in many zones.