Controls on pristine aerosol over the Southern Ocean (SO) are critical for constraining the strength of global aerosol indirect forcing. Observations of summertime SO clouds and aerosols in synoptically varied conditions during the 2018 SOCRATES aircraft campaign reveal novel mechanisms influencing pristine aerosol-cloud interactions. The SO free troposphere (3-6 km) is characterized by widespread, frequent new particle formation events contributing to much larger concentrations (≥ 1000 mg-1) of condensation nuclei (diameters > 0.01 μm) than in typical sub-tropical regions. Synoptic-scale uplift in warm conveyor belts and sub-polar vortices lifts marine biogenic sulfur-containing gases to free-tropospheric environments favorable for generating Aitken-mode aerosol particles (0.01-0.1 μm). Free-tropospheric Aitken particles subside into the boundary layer, where they grow in size to dominate the sulfur-based cloud condensation nuclei (CCN) driving SO cloud droplet number concentrations (Nd ~ 60-100 cm-3). Evidence is presented for a hypothesized Aitken-buffering mechanism which maintains persistently high summertime SO Nd against precipitation removal through CCN replenishment from activation and growth of boundary layer Aitken particles. Nudged hindcasts from the Community Atmosphere Model (CAM6) are found to underpredict Aitken and accumulation mode aerosols and Nd, impacting summertime cloud brightness and aerosol-cloud interactions and indicating incomplete representations of aerosol mechanisms associated with ocean biology.

An evaluation of three climate models is conducted using in situ airborne observations from the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) campaign. The evaluation targets cloud phases, microphysical properties, thermodynamic conditions, and aerosol indirect effects at -40°C – 0°C. For cloud phase frequency distribution, the Community Atmosphere Model version 6 (CAM6) shows the most similar result to the observations, which allows more liquid-containing clouds below -10°C compared with its predecessor – CAM5. The Energy Exascale Earth System Model (E3SM) underestimates (overestimates) ice phase frequencies below (above) -20°C. Compared with 580-second averaged observations (i.e., 100 km horizontal scale), CAM6 and E3SM overestimate (underestimate) liquid (ice) water content (i.e., LWC and IWC), leading to lower a glaciation ratio when ice and liquid coexist. Thermodynamic conditions, specifically relative humidity (RH), is likely a key factor contributing to model cloud occurrence and cloud phase biases. Simulated in-cloud RH shows higher minimum values than observations, possibly restricting ice growth during sedimentation. As number concentrations of larger and smaller aerosols (> 500 nm and > 100 nm) increase, observations show increases in glaciation ratio, cloud fraction, LWC and liquid number concentration (Nliq) at -18°C to 0°C, and IWC and ice number concentration (Nice) at -35°C to 0°C. CAM6 and E3SM show slight increases of LWC and Nliq, and E3SM shows small increases of Nice. These results indicate that models underestimate aerosol indirect effects on ice and mixed phase clouds over the Southern Ocean.

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.

Southern Ocean (SO) clouds are critical for climate prediction. Yet, previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in-situ observations, such as cloud location, cloud phase and boundary layer structure. The simulation in the latest versions of the model has improved its representation of SO clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Initial comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions are close to observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model’s representation of SO clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is critical because cloud feedbacks and climate sensitivity are sensitive to the representation of Southern Ocean clouds.

The COVID19 pandemic led to dramatic changes in economic activity in 2020. We use estimates of emissions changes for 2020 in two Earth System Models (ESMs) to simulate the impacts of the COVID19 economic changes. Ensembles of nudged simulations are used to separate small signals from meteorological variability. Reductions in aerosol and precursor emissions, chiefly Black Carbon (BC) and sulfate (SO$_4$), led to reductions in total anthropogenic aerosol cooling through aerosol-cloud interactions. The average overall Effective Radiative Forcing (ERF) peaks at +0.29$\pm$0.15 Wm$^{-2}$ in spring 2020. Changes in cloud properties are smaller than observed changes during 2020. Impacts of these changes on regional land surface temperature range up to +0.3K. The peak impact of these aerosol changes on global surface temperature is very small (+0.03K). However, the aerosol changes are the largest contribution to COVID19 emissions induced radiative forcing and temperature changes, dominating ozone, CO$_2$ and contrail effects.

We examine the response of the Community Earth System Model versions 1 and 2 (CESM1 and CESM2) to abrupt quadrupling of atmospheric CO$_2$ concentrations (4xCO2) and to 1% annually increasing CO2 concentrations (1%CO2). Different estimates of equilibrium climate sensitivity (ECS) for CESM1 and CESM2 are presented. All estimates show that the sensitivity of CESM2 has increased by 1.5K or more over that of CESM1. At the same time the transient climate response (TCR) of CESM1 and CESM2 derived from 1%CO2 experiments has not changed significantly - 2.1K in CESM1 and 2.0K in CESM2. Increased initial forcing as well as stronger shortwave radiation feedbacks are responsible for the increase in ECS seen in CESM2. A decomposition of regional radiation feedbacks and their contribution to global feedbacks shows that the Southern Ocean plays a key role in the overall behavior of 4xCO2 experiments, accounting for about 50% of the total shortwave feedback in both CESM1 and CESM2. The Southern Ocean is also responsible for around half of the increase in shortwave feedback between CESM1 and CESM2, with a comparable contribution arising over tropical ocean. Experiments using a thermodynamic slab-ocean model (SOM) yield estimates of ECS that are in remarkable agreement with those from fully-coupled earth system model (ESM) experiments for the same level of CO2 increase. Finally, we show that the similarity of TCR in CESM1 and CESM2 masks significant regional differences in warming that occur in the 1%CO2 experiments for each model.

Clouds are one of the most critical yet uncertain aspects of weather and climate prediction. The complex nature of sub-grid scale cloud processes makes traceable simulation of clouds across scales difficult (or impossible). Often models and measurements are used to develop empirical relationships for large-scale models to be computationally efficient. Machine learning provides another potential tool to improve our empirical parameterizations of clouds. To explore these opportunities, we replace the warm rain formation process in a General Circulation Model (GCM) with a detailed treatment from a bin microphysical model that causes a 400\% slowdown in the GCM. We analyze the changes in climate that result from the use of the bin microphysical calculation and find improvements in the rain onset and frequency of light rain compared to detailed models and observations. We also find a resulting change in the cloud feedback response of the model to warming, which will significantly impact the climate sensitivity. We then emulate this process with an emulator consisting of multiple neural networks that predict whether specific tendencies will be nonzero and the magnitude of the nonzero tendencies. We describe the risks of over-fitting, extrapolation, and linearization of a non-linear problem by using perfect model experiments with and without the emulator and show we can recover the solutions with the emulators in almost all respects, and recover nearly all the speed to get simulations that perform as the detailed model, but with the computational cost of the control simulation.

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.

This study uses cloud and radiative properties collected from in-situ and remote sensing instruments during two coordinated campaigns over the Southern Ocean between Tasmania and Antarctica in January-February 2018 to evaluate the simulations of clouds and precipitation in nudged-meteorology simulations with the CAM6 and AM4 global climate models sampled at the times and locations of the observations. Fifteen SOCRATES research flights sampled cloud water content, cloud droplet number concentration, and particle size distributions in mixed-phase boundary-layer clouds at temperatures down to -25 C. The six-week CAPRICORN2 research cruise encountered all cloud regimes across the region. Data from vertically-pointing 94 GHz radars deployed was compared with radar-simulator output from both models. Satellite data was compared with simulated top-of-atmosphere (TOA) radiative fluxes. Both models simulate observed cloud properties fairly well within the variability of observations. Cloud base and top in both models are generally biased low. CAM6 overestimates cloud occurrence and optical thickness while cloud droplet number concentrations are biased low, leading to excessive TOA reflected shortwave radiation. In general, low clouds in CAM6 precipitate at the same frequency but are more homogeneous compared to observations. Deep clouds are better simulated but produce snow too frequently. AM4 underestimates cloud occurrence but overestimates cloud optical thickness even more than CAM6, causing excessive outgoing longwave radiation fluxes but comparable reflected shortwave radiation. AM4 cloud droplet number concentrations match observations better than CAM6. Precipitating low and deep clouds in AM4 have too little snow. Further investigation of these microphysical biases is needed for both models.