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Abstract Simulating the Earth system is crucial for studying Earth's climate and how it changes. Modeling approaches that simplify the Earth system while retaining key characteristics are important tools to advance understanding. The simplicity and flexibility of idealized models enables imaginative science and makes them powerful educational tools. Evolving scientific community needs and increasing model complexity, however, makes it challenging to maintain and support idealized configurations in cutting‐edge Earth system modeling frameworks. We call on the scientific community to re‐emphasize model hierarchies within these frameworks to aid in understanding the Earth system, advancing model development, and developing the future workforce. 

Abstract Near-surface extreme winds profoundly affect human society, yet process-based understanding of their changes under climate forcings remains limited. This study systematically investigates the responses of high (HWE) and low (LWE) wind extremes (10-meter) to climate forcings using a hierarchy of climate model experiments from multiple general circulation models that participated in the Cloud Feedback Model Intercomparison Project. We analyze idealized atmosphere-only aquaplanet (Aqua) simulations and more realistic land-atmosphere (AMIP) simulations to identify robust responses to climate forcings and trace the sources of structural uncertainty. In Aqua simulations, tropical LWE changes exhibit large inter-model spread, which can be partly traced to model-dependent responses of low-pressure systems. In contrast, extratropical HWE intensify robustly with surface warming, linked to the strengthening of high-latitude extratropical cyclones. The AMIP simulations confirm the robust intensification of extratropical HWE. The more realistic boundary conditions in AMIP simulations act as a constraint, reducing inter-model spread in tropical zonal means compared to Aqua simulations. A comparison of uniform and patterned 4-K warming experiments suggests that the global magnitude of warming, rather than the specific warming pattern, dominates the large-scale responses of wind extremes. However, regional projections of extreme wind changes, especially over land, remain highly uncertain due to divergences in model formulations. Case studies reveal that major disagreements in HWE changes can stem from fundamental differences in representing the type and seasonality of extreme-producing weather systems. Our results underscore that reducing uncertainty in regional wind projections requires constraining the physical representation of weather systems in climate models. 

Abstract Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better‐informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open‐source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. We focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional‐refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm‐resolving model in precipitation predictions across scales. 

Abstract The Community Earth System Model, version 2 (CESM2), has a very high climate sensitivity driven by strong positive cloud feedbacks. To evaluate the simulated clouds in the present climate and characterize their response with climate warming, a clustering approach is applied to three independent satellite cloud products and a set of coupled climate simulations. Usingk-means clustering with a Wasserstein distance cost function, a set of typical cloud configurations is derived for the satellite cloud products. Using satellite simulator output, the model clouds are classified into the observed cloud regimes in both current and future climates. The model qualitatively reproduces the observed cloud configurations in the historical simulation using the same time period as the satellite observations, but it struggles to capture the observed heterogeneity of clouds which leads to an overestimation of the frequency of a few preferred cloud regimes. This problem is especially apparent for boundary layer clouds. Those low-level cloud regimes also account for much of the climate response in the late twenty-first century in four shared socioeconomic pathway simulations. The model reduces the frequency of occurrence of these low-cloud regimes, especially in tropical regions under large-scale subsidence, in favor of regimes that have weaker cloud radiative effects. 

Central North America is the global hotspot for tornadoes, fueled by elevated terrain of the Rockies to the west and a source of warm, moist air from equatorward oceans. This conventional wisdom argues that central South America, with the Andes to the west and Amazon basin to the north, should have a “tornado alley” at least as active as central North America. Central South America has frequent severe thunderstorms yet relatively few tornadoes. Here, we show that conventional wisdom is missing an important ingredient specific to tornadoes: a smooth, flat ocean-like upstream surface. Using global climate model experiments, we show that central South American tornado potential substantially increases if its equatorward land surface is smoothed and flattened to be ocean-like. Similarly, we show that central North American tornado potential substantially decreases if its equatorward ocean surface is roughened to values comparable to forested land. A rough upstream surface suppresses the formation of tornadic environments principally by weakening the poleward low-level winds, characterized by a weakened low-level jet east of the mountain range. Results are shown to be robust for any midlatitude landmass using idealized experiments with a simplified continent and mountain range. Our findings indicate that large-scale upstream surface roughness is likely a first-order driver of the strong contrast in tornado potential between North and South America. 

Abstract In the warm, equable climate of the Eocene, constraints on CO₂levels and low-latitude temperatures have generally precluded climate models from recreating key features of the climate, especially the above-freezing winter temperatures in the continental interiors suggested by fossil evidence of frost-intolerant species at high latitudes. Several cloud feedbacks have been suggested as mechanisms for enhanced wintertime warming, including a breakup of subtropical stratocumulus cloud decks at high CO₂concentrations. It has been suggested that this breakup could lead to 8 K of global average warming, but how this low-latitude cloud feedback translates to high-latitude warming is not obvious and warrants quantification with a global climate model. In this study, we use cloud-locking experiments in the Community Earth System Model, version 2 (CESM2), in which homogeneous subtropical stratocumulus clouds are prescribed or completely removed to investigate the maximum warming achieved by a breakup of subtropical stratocumulus clouds in both a preindustrial and a high CO₂climate. We use the present-day continental configuration and vegetation to make these results applicable to a future warm climate. We find that in the most dramatic case, the stratocumulus breakup leads to a significant globally averaged warming of about 4.5 K and contributes to some reduction in below-freezing days in the continental interiors at high latitudes. The resulting warming is limited by stabilizing low-cloud feedbacks induced elsewhere following the breakup. We conclude that a stratocumulus breakup may have played a nonnegligible role in past warm climates, even if it cannot, on its own, explain the key features of the Eocene. 

Abstract Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.