A convolutional neural network was used to detect occurrences of pockets of open cells (POCs). Trained on a small hand-logged dataset and applied to 13 years of satellite imagery the neural network is able to classify 8,491 POCs. This extensive database allows the first robust analysis of the spatial and temporal prevalence of these phenomena, as well as a detailed analysis of their micro-physical properties. We find a large (30%) increase in cloud effective radius inside POCs as compared to their surroundings and similarly large (20%) decrease in cloud fraction. This also allows their global radiative effect to be determined. Using simple radiative approximations we find that the instantaneous global mean top-of-atmosphere perturbation by all POCs is only 0.01Wm-2.

Many different emission pathways exist that are compatible with the Paris climate agreement, and many more are possible that miss that target. While some of the most complex Earth System Models have simulated a small selection of Shared Socioeconomic Pathways, it is impractical to use these expensive models to fully explore the space of possibilities. Such explorations therefore mostly rely on one-dimensional impulse response models, or simple pattern scaling approaches to approximate the physical climate response to a given scenario. Here we present ClimateBench - a benchmarking framework based on a suite of CMIP, AerChemMIP and DAMIP simulations performed by a full complexity Earth System Model, and a set of baseline machine learning models that emulate its response to a variety of forcers. These emulators can predict annual mean global distributions of temperature, diurnal temperature range and precipitation (including extreme precipitation) given a wide range of emissions and concentrations of carbon dioxide, methane and aerosols, allowing them to efficiently probe previously unexplored scenarios. We discuss the accuracy and interpretability of these emulators and consider their robustness to physical constraints such as total energy conservation. Future opportunities incorporating such physical constraints directly in the machine learning models and using the emulators for detection and attribution studies are also discussed. This opens a wide range of opportunities to improve prediction, consistency and mathematical tractability. We hope that by laying out the principles of climate model emulation with clear examples and metrics we encourage others to tackle this important and demanding challenge.

Convective aggregation is an important atmospheric phenomenon which frequently occurs in idealised models in radiative-convective equilibrium (RCE), where the effects of land, rotation, sea surface temperature gradients, and the diurnal cycle are often removed. This aggregation is triggered and maintained by self-generated radiatively driven circulations, for which longwave feedbacks are essential. Many questions remain over how important the driving processes of aggregation in idealized models are in the real atmosphere. We approach this question by adding a continentally-sized, idealized tropical rainforest island into an RCE model to investigate how land-sea contrasts impact convective aggregation and its mechanisms. We show that convection preferentially forms over the island persistently in our simulation. This is forced by a large-scale thermally driven circulation. First, a sea-breeze circulation is triggered by the land-sea thermal contrast, driven by surface sensible heating. This sea-breeze circulation triggers convection which then generates longwave heating anomalies. We find that these longwave heating anomalies are essential for maintaining the aggregation of convection over the island through mechanism denial tests. We also show, by varying the island size, that the aggregated convective cluster appears to have a maximum spatial extent of 10,000 km. These results highlight that the mechanisms of idealized aggregation remain relevant when land is included in the model, and therefore these mechanisms could help us understand convective organization in the real-world.

By interacting with radiation, aerosols perturb the Earth’s energy budget and thus the global precipitation amount. It was previously shown that aerosols lead to a reduction in the global-mean precipitation amount. We have further demonstrated in aqua-planet simulations that the local response to absorbing aerosols differs between the tropics and the extra-tropics. In this study we incorporate an energy budget perspective to further examine the latitudinal dependence of the effect of aerosol-radiation interaction on precipitation in idealized global simulations. We demonstrate that the transition between a positive local precipitation response in the tropics and a negative local precipitation response in the extra-tropics occurs at relatively low latitudes (~10), indicating a transition between the deep-tropics (in which the Coriolis force is low, hence direct thermally-driven circulation, and associated divergence/convergence of energy/moisture, can form as a result of the diabatic-heating) and their surroundings. In addition, we gradually increase the level of complexity of the simulations and demonstrate that, in the case of absorbing aerosols, the effect of land is to counteract some of the response both inside and outside the deep-tropics due to the reduction in surface latent-heat flux that opposes the diabatic-heating. The effect of scattering aerosols is also examined and demonstrate a decrease in precipitation over land in both the tropics and extra-tropics and no effect over the ocean. Finally, we examine these results in a more realistic set-up and demonstrate that although the physical mechanisms still operate, they are unlikely to be significant enough to be discerned from natural-variability.

Absorbing aerosol from biomass burning impacts the hydrological cycle and fluxes of radiation both directly and indirectly via modifications to convective processes and cloud development. Using the ICON model in a regional configuration with convection-permitting resolution of 1500 m, we isolate the response of the Amazonian atmosphere to biomass burning smoke via enhanced cloud droplet number concentrations Nd (aerosol-cloud-interactions; ACI) and changes to radiative fluxes (aerosol-radiation-interactions; ARI). We decompose ARI into contributions from surface cooling (reduced surface shortwave flux) and localized heating of the smoke layer. We show that ARI influences the formation and development of convective cells: surface cooling below the smoke drives suppression of convection that increases with the smoke optical depth, whilst the elevated heating promotes initial suppression and subsequent intensification of convection overnight; a corresponding diurnal response from high precipitation rates is shown. Enhanced Nd (ACI) perturbs the intensive cloud properties and suppresses low-to-moderate precipitation rates. Both ACI and ARI result in enhanced high-altitude ice clouds that have a strong positive longwave radiative effect. Changes to low-cloud coverage (ARI) and albedo (ACI) drive an overall negative shortwave radiative effect, that slowly increases in magnitude due to a moistening of the boundary layer. The overall net radiative effect is dominated by the enhanced high-altitude clouds, and is sensitive to the plume longevity. The considerable diurnal responses that we simulate cannot be observed by polar orbiting satellites widely used in previous work, highlighting the potential of geostationary satellites to observe large-scale impacts of aerosols on clouds.

The uncertainty in present-day anthropogenic forcing is dominated by uncertainty in the strength of the contribution from aerosol. Much of the uncertainty in the direct aerosol forcing can be attributed to uncertainty in the anthropogenic fraction of aerosol in the present-day atmosphere, due to a lack of historical observations. Here we present a robust relationship between total present-day aerosol optical depth and the anthropogenic contribution across two multi-model ensembles and a large single-model perturbed parameter ensemble. Using observations of aerosol optical depth, we determine a reduced likely range of the anthropogenic component and hence a reduced uncertainty in the direct forcing of aerosol.

Quantifying Effective Radiative Forcing due to aerosol-cloud interactions (ERFACI) remains a largely uncertain process, and the magnitude remains unconstrained in general circulation models. Previous studies focus on the magnitude of ERFACI arising from all cloud types, or examine it in the framework of dynamical regimes. Aerosol forcing due to aerosol-cloud interactions in the HadGEM3-GA7.1 global climate model is decomposed into several global observational cloud regimes. Regimes are allocated to model gridboxes and forcing due to aerosol-cloud interactions is calculated on a regime-by-regime basis with a 20-year meaning period. Patterns of regime occurrence are in good agreement with satellite observations. ERFACI is then further decomposed into three terms, representing radiative changes within a given regime, transitions between different cloud regimes, and nonlinear effects. The total global mean ERFACI is -1.8 Wm-2. When decomposed, simulated ERFACI is greatest in the stratocumulus regime (-0.75 Wm-2).

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth’s radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This poster presents the outcome of an international workshop and subsequent review paper, which quantify the likely range of aerosol radiative forcing over the industrial era based on multiple lines of evidence, including modelling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes narrow the range of the forcing from aerosol-radiation interactions compared to the latest assessment by the Intergovernmental Panel on Climate Change (IPCC). A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction and on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to total aerosol radiative forcing ranges that are of similar width to the last IPCC assessment but more clearly based on physical arguments.