This study investigates low cloud feedback in a warmer climate using global simulations from the high-resolution multi-scale modeling framework (HR-MMF), which explicitly simulates small-scale eddies globally. Two, five-year simulations — one with present-day sea surface temperatures (SSTs) and a second with SSTs warmed uniformly by 4 K — reveal a positive global shortwave cloud radiative effect (SWCRE = 0.3 W/m^2/K), comparable to estimates from CMIP models. As the climate warms, significant reductions in low cloud cover occur over stratocumulus regions. This study is the first attempt to compare HR-MMF results with predictions from idealized large-eddy simulations from the CGILS intercomparison. Despite different underlying assumptions, we find qualitative agreement in SWCRE and inversion height changes between HR-MMF and CGILS predictions. This suggests reasonable credibility for the CGILS framework in predicting cloud responses under the out-of-sample conditions found in HR-MMF. However, the HR-MMF exhibits stronger SWCRE changes than predicted by CGILS. We explore potential causes for this discrepancy, examining variations in cloud-controlling factors (CCFs) and cloud conditions. Our results show a fairly homogeneous SWCRE response, with little systematic variation tied to the variations in CCFs. This reveals a dominant role for SST forcing in modulating SWCRE.

Localized tropical rainfall changes commonly occur on 500-1,000 km scales under many climate forcings, but understanding their causality is notoriously challenging. One helpful process-oriented diagnostic (POD) decomposes the effects of undilute buoyancy and mid-level moisture through a precipitation-buoyancy relationship, but its applicability at these scales is uncertain. In this context, we examine month-to-month changes in five subregional "hotspots" of the South Asian monsoon. While the POD qualitatively explains month-to-month rainfall, revealed variability in the precipitation-buoyancy relationship leads to underprediction of rainfall changes by 18-90%. Encouragingly, in a subset of subregions with minimal variability, the POD successfully identifies how shifts in the large-scale thermodynamic environment drive rainfall changes, highlighting the role of mid-level moisture in modulating monsoon onset. We encourage the same methodology be broadly applied to interpret thermodynamic drivers of similarly localized precipitation changes that occur in climate model predictions of warming, aerosol effects, geoengineering, and ENSO.

Vertical resolution is an often overlooked parameter in simulations of convection. We explore the sensitivity of simulated deep convection to vertical resolution in the System for Atmospheric Modeling (SAM) convection resolving model. We analyze simulations run in tropical radiative convective equilibrium with 32, 64, 128, and 256 vertical levels in a small (100 km) and large domain (1500 km). At high vertical resolution, the relative humidity and anvil cloud fraction are reduced, which is linked to a reduction in both fractional and volumetric detrainment. This increases total atmospheric radiative cooling at high resolution, which leads to enhanced surface fluxes and precipitation, despite reduced column water vapor. In large domains, convective aggregation begins by simulation day 25 for simulations with 64 and 128 levels, while onset is delayed until simulation day 75 for the simulation with 32 vertical levels. Budget analyses reveal that mechanisms involved in the generation and maintenance of convective aggregation for the 32-level simulation differ from those for the 64- and 128-level simulations. Weaker cold pools in the 32-level simulation allow the boundary layer in dry regions to become extremely dry, which leads to an aggregated state with very strong spatial gradients in column-integrated moist static energy. Understanding both the triggering and maintenance of convective aggregation and its simulated sensitivity to model formulation is a necessary component of atmospheric modeling. We show that vertical resolution has a strong impact on the mean state and convective behavior in both small and large domains.