The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-like events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. These results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.

In this study, an aerosol-dependent ice nucleation scheme has been implemented in an aerosol-enabled Multiscale Modeling Framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10-100/L) at cirrus temperatures. The new model simulates the observed shift of the ice supersaturation PDF toward higher values at low temperatures following the homogeneous nucleation threshold. The MMF model predicts a higher frequency of midlatitude supersaturation in the Southern Hemisphere and winter hemisphere, which is consistent with previous satellite and in situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to simulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation scheme and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement with the satellite-retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state-of-the-art global climate models (GCM), especially those in which embedded cloud-resolving models replace conventional statistical parameterizations (i.e., multiscale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre-industrial and present-day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten-year GCM simulations with nudging provide a more stable estimate of the global-annual mean net aerosol indirect radiative forcing than do conventional free-running simulations. The estimates have mean values and 95% confidence intervals of −1.19 ± 0.02 W/m² and −1.37 ± 0.13 W/m²for nudged and free-running simulations, respectively. Nudging also substantially increases the fraction of the world's area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earth's surface for nudged and free-running simulations, respectively). One-year MMF simulations with and without nudging provide global-annual mean net aerosol indirect radiative forcing estimates of −0.81 W/m² and −0.82 W/m², respectively. These results compare well with previous estimates from three-year free-running MMF simulations (−0.83 W/m²), which showed the aerosol-cloud relationship to be in better agreement with observations and high-resolution models than in the results obtained with conventional cloud parameterizations.

Abstract. New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOM chemistry. Here, we incorporate a state-of-the-art biogenic HOM chemistry scheme with 96 chemical reactions to a global chemistry–climate model and quantify the contribution to global aerosols through HOM-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from −96 % to −15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that compared to turning off the organic nucleation rate, turning off organic initial growth results in a more substantial decrease in aerosol number concentrations. Globally, organics contribute around 45 % of the annual mean vertically integrated nucleation rate (at 1.7 nm) and 25 % of the vertically averaged growth rate. The inclusion of HOM-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the semi-explicit HOM mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make aerosol sensitive to changes in biogenic emissions.

Low clouds play a key role in the Earth-atmosphere energy balance and influence agricultural production and solar-power generation. Smoke aloft has been found to enhance marine stratocumulus through aerosol-cloud interactions, but its role in regions with strong human activities and complex monsoon circulation remains unclear. Here we show that biomass burning aerosols aloft strongly increase the low cloud coverage over both land and ocean in subtropical southeastern Asia. The degree of this enhancement and its spatial extent are comparable to that in the Southeast Atlantic, even though the total biomass burning emissions in Southeast Asia are only one-fifth of those in Southern Africa. We find that a synergetic effect of aerosol-cloud-boundary layer interaction with the monsoon is the main reason for the strong semi-direct effect and enhanced low cloud formation in southeastern Asia.