Cirrus clouds of various thicknesses and radiative characteristics extend over much of the tropics, especially around deep convection. They can be difficult to observe due to their high altitude and sometimes small optical depths. They are also difficult to simulate in conventional global climate models, which have coarse grid spacings and simplified parameterizations of deep convection and cirrus formation. We investigate the representation of tropical cirrus in global storm-resolving models (GSRMs), which have higher spatial resolution and explicit convection and could more accurately represent cirrus cloud processes. This study uses GSRMs from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project. The aggregate life cycle of tropical cirrus is analyzed using joint albedo and outgoing longwave radiation (OLR) histograms to assess the fidelity of models in capturing the observed cirrus cloud populations over representative tropical ocean and land regions. The proportions of optically-thick deep convection, anvils, and cirrus vary across models and are reflected in the vertical distribution of cloud cover and top-of-atmosphere radiative fluxes. Model differences in cirrus populations, likely driven by subgrid processes such as ice microphysics, dominate over regional differences between convectively-active tropical land and ocean locations.

We design a new strategy to load-balance high-intensity sub-grid atmospheric physics calculations restricted to a small fraction of a global climate simulation’s domain. We show why the current parallel load balancing infrastructure of CESM and E3SM cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud-resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high-resolution (MMF-HR; sub-km horizontal grid spacing) relative to standard low-resolution (MMF-LR) cloud superparameterization elsewhere. To enable MMF runs with Multi-Domain CRMs, our load balancing theory predicts the most efficient computational scale as a function of the high-intensity work’s relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high-intensity (and rate-limiting) HR grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/LR CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real-geography settings. As intended, within the high (low) resolution area, our Multi-Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF-LR and MMF-HR. We suggest this approach can open up a range of creative multi-resolution climate experiments without requiring unduly large allocations of computational resources.

A new Aitken mode aerosol scheme is developed for a large eddy simulation (LES) model in order to better investigate cloud-aerosol interactions in the marine boundary layer and to study the Aitken buffering hypothesis of McCoy et al. (2021). This scheme extends the single-mode two-moment prognostic aerosol scheme of Berner et al. (2013). Nine prognostic variables represent accumulation and Aitken log-normal aerosol modes in air and droplets as well as 3 gas species. Scavenging of interstitial aerosol by cloud and rain drops and coagulation of dry aerosol are treated using the scheme described in B13. The scheme includes a simple chemistry model with gas phase H2SO4, SO2, and DMS as prognostic variables to capture basic influences of sulfur chemistry on the model aerosols. Primary nucleation of H2SO4 aerosol particles from gas-phase H2SO4 is neglected. A deep, precipitating stratocumulus case (VOCALS RF06) is used to test the new scheme. The presence of the Aitken mode aerosol increases the cloud droplet concentration through activation of the larger Aitken particles and delays the creation of an ultraclean, strongly precipitating cumulus state. Scavenging of dry accumulation and Aitken particles by cloud and precipitation droplets accelerates the collapse. Increasing either the above-inversion Aitken concentration or the surface Aitken flux increases the Aitken population in the boundary layer and prevents the transition to an ultraclean state.

One way to test our understanding of the impact of convective processes on the isotopic composition of water vapor and precipitation is to analyze the isotopic mesoscale variations during organized convective systems such as tropical cyclones or squall lines. The goal of this study is to understand these isotopic mesoscale variations with particular attention to isotopic signals in near-surface vapor and precipitation that may be present in observations and in paleoclimate proxies. With this aim, we run cloud resolving model simulations in radiative-convective equilibrium in which rotation or wind shear is added, allowing us to simulate tropical cyclones or squall lines. The simulations capture the robust aspects of mesoscale isotopic variations in observed cyclones and squall lines. We interpret these variations using a simple water budget model for the sub-cloud layer of different parts of the domain. We find that rain evaporation and rain-vapor diffusive exchanges are the main drivers of isotopic depletion within cyclones and squall lines. Horizontal advection spreads isotopic anomalies, thus reshaping the mesoscale isotopic pattern. Variations in near-surface relative humidity and wind speed have a significant impact on d-excess variations within tropical cyclones, but the evaporation of sea spray is not necessary to explain the observed enrichment in the eye. This study strengthens our understanding of mesoscale isotopic variability and provides physical arguments supporting the interpretation of paleoclimate isotopic archives in tropical regions in terms of past cyclonic activity.

The goal of this study is twofold. First, we aim at developing a simple model as an interpretative framework for the water vapor isotopic variations in the tropical troposphere over the ocean. We use large-eddy simulations to justify the underlying assumptions of this simple model, to constrain its input parameters and to evaluate its results. Second, we aim at interpreting the depletion of the water vapor isotopic composition in the lower and mid-troposphere as precipitation increases, which is a salient feature in tropical oceanic observations. This feature constitutes a stringent test on the relevance of our interpretative framework. Previous studies, based on observations or on models with parameterized convection, have highlighted the roles of deep convective and meso-scale downdrafts, rain evaporation, rain-vapor diffusive exchanges and mixing processes. The interpretative framework that we develop is a two-column model representing the net ascent in clouds and the net descent in the environment. We show that the mechanisms for depleting the troposphere when precipitation rate increases all stem from the higher tropospheric relative humidity. First, when the relative humidity is larger, less snow sublimates before melting and a smaller fraction of rain evaporates. Both effects lead to more depleted rain evaporation and eventually more depleted water vapor. This mechanism dominates in regimes of large-scale ascent. Second, the entrainment of dry air into clouds reduces the vertical isotopic gradient and limits the depletion of tropospheric water vapor. This mechanism dominates in regimes of large-scale descent.

Climate models struggle to accurately represent the highly reflective boundary layer clouds overlying the remote and stormy Southern Ocean. We use in-situ aircraft observations from the Southern Ocean Clouds, Radiation and Aerosol Transport Experimental Study (SOCRATES) to evaluate Southern Ocean clouds in a cloud-resolving large-eddy simulation (LES) and two coarse resolution global atmospheric models, the CESM Community Atmosphere Model (CAM6) and the GFDL global atmosphere model (AM4), run in a nudged hindcast framework. We develop six case studies from SOCRATES data which span the range of observed cloud and boundary layer properties. For each case, the LES is run once forced purely using reanalysis data (‘ERA5-based’) and once strongly nudged to an aircraft profile (‘Obs-based’). The ERA5-based LES can be compared with the global models, which are also nudged to reanalysis data, and is better for simulating cumulus. The Obs-based LES closely matches an observed cloud profile and is useful for microphysical comparisons and sensitivity tests, and simulating multi-layer stratiform clouds. We use two-moment Morrison microphysics in the LES and find that it simulates too few frozen particles in clouds occurring within the Hallett-Mossop temperature range. We modify the Hallett-Mossop parameterization so that it activates within boundary layer clouds and we achieve better agreement between observed and simulated microphysics. The nudged GCMs achieve reasonable supercooled liquid water dominated clouds in most cases but struggle to represent multi-layer stratiform clouds and to maintain liquid water in cumulus clouds. CAM6 has low droplet concentrations in all cases and underestimates stratiform cloud-driven turbulence.

Cirrus control the longwave radiative budget of the tropics. For the first time, we quantify the variability in cirrus properties and longwave cloud radiative effects (CREs) that arises from using different bulk ice microphysical parameterizations within a single global storm-resolving model. We run five-day meteorologically-nudged simulations with four commonly-used microphysics schemes (M2005, Thompson, P3 and SAM1MOM) and evaluate them with satellite products and in situ observations. Tropical average longwave CRE varies over 20 W m$^{-2}$ between schemes. Within the Thompson scheme, rapid autoconversion of cloud ice to snow leads to deficient anvil cirrus even with radiatively active snow. SAM1MOM, which uses saturation adjustment for cloud ice, also has deficient anvil cirrus. M2005 and P3 simulate cirrus with realistic frozen water path, and P3 best reproduces observed longwave CRE. Even in those schemes, ice crystal number concentrations commonly hit limiters and lack the observed variability and dependence on frozen water content.

The extension of a cloud-resolving model, the System for Atmospheric Modeling (SAM), to global domains is described. The resulting global model, gSAM, is formulated on a latitude-longitude grid. It uses an anelastic dynamical core with a single reference profile (as in SAM), but its governing equations differ somewhat from other anelastic models. For quasi-hydrostatic flows, they are isomorphic to the primitive equations in pressure coordinates, but with the globally uniform reference pressure playing the role of actual pressure. As a result, gSAM can exactly maintain steady zonally symmetric baroclinic flows that have been specified in pressure coordinates, produces accurate simulations when initialized or nudged with global reanalyses, and has a natural energy conservation equation, despite the drawbacks of using the anelastic system to model global scales. gSAM employs a novel treatment of topography using a type of immersed boundary method, the Quasi-Solid Body Method (QSBM), where the instantaneous flow velocity is forced to stagnate in grid cells inside prescribed terrain. The results of several standard tests designed to evaluate accuracy of global models with and without topography as well as results from real-Earth simulations are presented.

Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top-of-atmosphere radiation balance and stratospheric water vapor budget. These cirrus are often associated with deep convection, which global climate models must parameterize and struggle to accurately simulate. By comparing high-resolution global storm-resolving models from the Dynamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) intercomparison that explicitly simulate deep convection to satellite observations, we assess how well these models simulate deep convection, convectively generated cirrus, and deep convective injection of water into the TTL over representative tropical land and ocean regions. The DYAMOND models simulate deep convective precipitation, organization, and cloud structure fairly well over land and ocean regions, but with clear intermodel differences. All models produce frequent overshooting convection whose strongest updrafts humidify the TTL and are its main source of frozen water. Inter-model differences in cloud properties and convective injection exceed differences between land and ocean regions in each model. We argue that global storm-resolving models can better represent tropical cirrus and deep convection in present and future climates than coarser-resolution climate models. To realize this potential, they must use available observations to perfect their ice microphysics and dynamical flow solvers.

Sub-kilometer processes are critical to the physics of aerosol-cloud interaction but have been dependent on parameterizations in global model simulations. We thus report the strength of aerosol-cloud interaction in the Ultra-Parameterized Community Atmosphere Model (UPCAM), a multiscale climate model that uses coarse exterior resolution to embed explicit cloud resolving models with enough resolution (250-m horizontal, 20-m vertical) to quasi-resolve sub-kilometer eddies. To investigate the impact on aerosol-cloud interactions, UPCAMâ\euro™s simulations are compared to a coarser multi-scale model with 3 km horizontal resolution. UPCAM produces cloud droplet number concentrations ($N_\mathrm{d}$) and cloud liquid water path (LWP) values that are higher than the coarser model but equally plausible compared to observations. Our analysis focuses on the Northern Hemisphere midlatitude oceans, where historical aerosol increases have been largest. We find similarities in the overall radiative forcing from aerosol-cloud interactions in the two models, but this belies fundamental underlying differences. The radiative forcing from increases in LWP is weaker in UPCAM, whereas the forcing from increases in $N_\mathrm{d}$ is larger. Surprisingly, the weaker LWP increase is not due to a weaker increase in LWP in raining clouds, but a combination of weaker increase in LWP in non-raining clouds and a smaller fraction of raining clouds in UPCAM. The implication is that as global modeling moves towards finer than storm-resolving grids, nuanced model validation of ACI statistics conditioned on the existence of precipitation and good observational constraints on the baseline probability of precipitation will become key for tighter constraints and better conceptual understanding.

The isotopic composition of water vapor (e.g. its Deuterium content) evolves along the water cycle as phase changes are associated with isotopic fractionation. In the tropics, it is especially sensitive to convective processes. Consequently the isotopic composition of precipitation recorded in paleoclimate archives has significantly contributed to the reconstruction of past hydrological changes. It has also been suggested that observed isotopic composition of water vapor could help better understand convective processes and evaluate their representation in climate models. Yet, water isotopes remain rarely used beyond the isotopic community to answer today’s pressing climate questions. A prerequisite to better assess the strengths and weaknesses of the isotopic tool is to better understand what controls spatio-temporal variations in water vapor isotopic composition through the tropical atmosphere. A first step towards this better understanding is to understand what controls the isotopic composition of the sub-cloud layer water vapor over the ocean. Isotopic measurements show that the water vapor is the most enriched in trade-wind regions, and becomes more depleted as precipitation increases. To understand this pattern, we use global simulations with the isotope-enabled general circulation model LMDZ, large-eddy simulation in radiative-convective equilibrium and with large-scale ascent or descent, with the isotope-enabled model SAM and simple analytical models. We show that increased precipitation rate is associated with increased isotopic depletion if it is associated with stronger large-scale ascent, but with decreased isotopic depletion if it is associated with warmer surface temperature. As large-scale ascent increases, the isotopic vertical gradient in the lower troposphere is steeper, which makes downdrafts and updrafts more efficient in depleting the sub-cloud layer water vapor. The steeper gradient is caused mainly by the larger quantity of snow falling down to the melting level, forming rain whose evaporation depletes the water vapor.