Global clusters are derived by applying the self‐organizing map technique to the Moderate Resolution Imaging Spectroradiometer cloud top pressure‐cloud optical thickness joint histograms. These cloud clusters are then used to classify Cloud Feedback Model Intercomparison Project Observation Simulator Package output from the HadGEM3 (Global Atmosphere version 7) atmosphere‐only climate model. Discrepancies in the Global Atmosphere version 7 representation of particular clusters can be established by examining the two sets of cluster's occurrence rate and radiative effect. The overall differences in the occurrence rates show major discrepancies in several of the clusters, resulting in a shift from five dominant clusters in Moderate Resolution Imaging Spectroradiometer (above 10% occurrence rate) to two dominant clusters in the model. A comparison of the geographic distributions of occurrence rate shows that the differences are strongly regional and unique to each cluster. While comparisons of the global mean longwave and shortwave cloud radiative effect (CRE) show strong agreement, examination of the CRE of individual cloud types reveals larger errors that highlight the role of compensating errors in masking model deficiencies. CRE data for each of the clusters is further partitioned into regions. This establishes that the bias associated with a cluster is highly variable globally, with no clusters showing consistent biases across all regions. Therefore, regional level phenomena likely play an important role in the creation of these errors.

This study explores the application of the self‐organizing map (SOM) methodology to cloud classification. In particular, the SOM is applied to the joint frequency distribution of the cloud top pressure and optical depth from the International Satellite Cloud Climatology Project (ISCCP) D1 data set. We demonstrate that this scheme produces clusters which have geographical and seasonal patterns similar to those produced in previous studies using the k‐means clustering technique but potentially provides complementary information. For example, this study identifies a wider range of clusters representative of low cloud cover states with distinct geographic patterns. We also demonstrate that two rather similar clusters, which might be considered the same cloud regime in other classifications, are distinct based on the seasonal variation of their geographic distributions and their cloud radiative effect in the shortwave. Examination of the transitions between regimes at particular geographic positions between one day and the next also shows that the SOM produces an objective organization of the various cloud regimes that can aid in their interpretation. This is also supported by examination of the SOM's Sammon map and correlations between neighboring nodes geographic distributions. Ancillary ERA‐Interim reanalysis output also allows us to demonstrate that the clusters, identified based on the joint histograms, are related to an ordered continuum of vertical velocity profiles and two‐dimensional vertical velocity versus lower tropospheric stability histograms which have a clear structure within the SOM. The different nodes can also be separated by their longwave and shortwave cloud radiative effect at the top of the atmosphere.

Abstract. In recent years, airborne microplastics have been identified in a range of remote environments. However, data throughout the Southern Hemisphere, in particular Antarctica, are largely absent to date. We collected snow samples from 19 sites across the Ross Island region of Antarctica. Suspected microplastic particles were isolated and their composition confirmed using micro-Fourier transform infrared spectroscopy (µFTIR). We identified microplastics in all Antarctic snow samples at an average concentration of 29 particles L−1, with fibres the most common morphotype and polyethylene terephthalate (PET) the most common polymer. To investigate sources, backward air mass trajectories were run from the time of sampling. These indicate potential long-range transportation of up to 6000 km, assuming a residence time of 6.5 d. Local sources were also identified as potential inputs into the environment as the polymers identified were consistent with those used in clothing and equipment from nearby research stations. This study adds to the growing body of literature regarding microplastics as a ubiquitous airborne pollutant and establishes their presence in Antarctica.

Abstract. With low concentrations of tropospheric aerosol, the Southern Ocean offers a “natural laboratory” for studies of aerosol–cloud interactions. Aerosols over the Southern Ocean are produced from biogenic activity in the ocean, which generates sulfate aerosol via dimethylsulfide (DMS) oxidation, and from strong winds and waves that lead to bubble bursting and sea spray emission. Here, we evaluate the representation of Southern Ocean aerosols in the Hadley Centre Global Environmental Model version 3, Global Atmosphere 7.1 (HadGEM3-GA7.1) chemistry–climate model. Compared with aerosol optical depth (AOD) observations from two satellite instruments (the Moderate Resolution Imaging Spectroradiometer, MODIS-Aqua c6.1, and the Multi-angle Imaging Spectroradiometer, MISR), the model simulates too-high AOD during winter and too-low AOD during summer. By switching off DMS emission in the model, we show that sea spray aerosol is the dominant contributor to AOD during winter. In turn, the simulated sea spray aerosol flux depends on near-surface wind speed. By examining MODIS AOD as a function of wind speed from the ERA-Interim reanalysis and comparing it with the model, we show that the sea spray aerosol source function in HadGEM3-GA7.1 overestimates the wind speed dependency. We test a recently developed sea spray aerosol source function derived from measurements made on a Southern Ocean research voyage in 2018. In this source function, the wind speed dependency of the sea spray aerosol flux is less than in the formulation currently implemented in HadGEM3-GA7.1. The new source function leads to good agreement between simulated and observed wintertime AODs over the Southern Ocean; however, it reveals partially compensating errors in DMS-derived AOD. While previous work has tested assumptions regarding the seawater climatology or sea–air flux of DMS, we test the sensitivity of simulated AOD, cloud condensation nuclei and cloud droplet number concentration to three atmospheric sulfate chemistry schemes. The first scheme adds DMS oxidation by halogens and the other two test a recently developed sulfate chemistry scheme for the marine troposphere; one tests gas-phase chemistry only, while the second adds extra aqueous-phase sulfate reactions. We show how simulated sulfur dioxide and sulfuric acid profiles over the Southern Ocean change as a result and how the number concentration and particle size of the soluble Aitken, accumulation and coarse aerosol modes are affected. The new DMS chemistry scheme leads to a 20 % increase in the number concentration of cloud condensation nuclei and cloud droplets, which improves agreement with observations. Our results highlight the importance of atmospheric chemistry for simulating aerosols and clouds accurately over the Southern Ocean.

<p><strong>Abstract.</strong> With low concentrations of tropospheric aerosol, the Southern Ocean offers a <q>natural laboratory</q> for studies of aerosol-cloud interactions. Aerosols over the Southern Ocean are produced from biogenic activity in the ocean, which generates sulfate aerosol via dimethylsulfide (DMS) oxidation, and from strong winds and waves that lead to bubble bursting and sea-spray emission. Here we evaluate the representation of Southern Ocean aerosols in the HadGEM3-GA7.1 chemistry-climate model. Compared with aerosol optical depth (AOD) observations from two satellite instruments (the Moderate Resolution Imaging Spectroradiometer, MODIS-Aqua c6.1 and the Multi-angle Imaging Spectroradiometer, MISR), the model simulates too-high AOD during winter and too-low AOD during summer. By switching off DMS emission in the model, we show that sea spray aerosol is the dominant contributor to AOD during winter. In turn, the simulated sea spray aerosol flux depends on near-surface wind speed. By examining MODIS AOD as a function of wind speed from the ERA-Interim reanalysis and comparing it with the model, we show that the sea spray aerosol source function in HadGEM3-GA7.1 overestimates the wind speed dependency. We test a recently-developed sea spray aerosol source function derived from measurements made on a Southern Ocean research voyage in 2018. In this source function the wind speed dependency of the sea spray aerosol flux is less than in the formulation currently implemented in HadGEM3-GA7.1. The new source function leads to good agreement between simulated and observed wintertime AOD over the Southern Ocean, however reveals partially compensating errors in DMS-derived AOD. While previous work has tested assumptions regarding the seawater climatology or sea-air flux of DMS, we test the sensitivity of simulated AOD, cloud condensation nuclei and cloud droplet number concentration to three atmospheric sulfate chemistry schemes. The first scheme adds DMS oxidation by halogens and the other two test a recently-developed sulfate chemistry scheme for the marine troposphere; one tests gas-phase chemistry only while the second adds extra aqueous-phase sulfate reactions. We show how simulated sulfur dioxide and sulfuric acid profiles over the Southern Ocean change as a result, and how the number concentration and particle size of the soluble Aitken, accumulation and coarse aerosol modes are affected. The new DMS chemistry scheme leads to a 20 % increase in the number concentration of cloud condensation nuclei and cloud droplets, which improves agreement with observations. Our results highlight the importance of atmospheric chemistry for simulating aerosols and clouds accurately over the Southern Ocean.</p>