Abstract. Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc. Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.

Abstract. Spatial and temporal profiles of chlorine dioxide (OClO), bromine monoxide (BrO) and sulfur dioxide (SO 2 ) of the volcanic plume at Mt. Etna, Italy, were investigated in September 2012 using Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS). OClO was detected in 119 individual measurements covering plume ages up to 6 min. BrO could be detected in 452 spectra up to 23 min downwind. The retrieved slant column densities (SCDs) reached maximum values of 2.0 × 10 14 molecules cm −2 (OClO) and 1.1 × 10 15 molecules cm −2 (BrO). Mean mixing ratios of BrO and OClO were estimated assuming a circular plume cross section. Furthermore, ClO mixing ratios were derived directly from the BrO and OClOSCDs. Average abundances of BrO = 1.35 ppb, OClO = 300 ppt and ClO = 139 ppt were found in the young plume (plume age τ < 4 min) with peak values of 2.7 ppb (BrO), 600 ppt (OClO) and 235 ppt (ClO) respectively.The chemical evolution of BrO and OClO in the plume was investigated in great detail by analysing the OClO/SO 2 and BrO/SO 2 ratios as a function of plume age τ . A marked increase of both ratios was observed in the young plume (τ < 142 s) and a levelling off at larger plume ages showing mean SO 2 ratios of 3.17 × 10 −5 (OClO/SO 2 ) and 1.65 × 10 −4 (BrO/SO 2 ). OClO was less abundant in the plume compared to BrO with a mean OClO/BrO ratio of 0.16 at plume ages exceeding 3 min.A measurement performed in the early morning at low solar radiances revealed BrO/SO 2 and OClO/SO 2 ratios increasing with time. This observation substantiates the importance of photochemistry regarding the formation of BrO and OClO in volcanic plumes.These findings support the current understanding of the underlying chemistry, namely, that BrO is formed in an autocatalytic, heterogeneous reaction mechanism (in literature often referred to as "bromine explosion") and that OClO is formed in the reaction of ClO with BrO.These new findings, especially the very detailed observation of the BrO and OClO formation in the young plume, were used to infer the prevailing Cl-atom concentrations in the plume. Relatively small values ranging from [Cl] = 2.5 × 10 6 cm −3 (assuming 80 ppb background O 3 ) to [Cl] = 2.0 × 10 8 cm −3 (at 1 ppb O 3 ) were calculated at plume ages of about 2 min. Based on these Cl abundances, a potentialchlorine-induced -depletion of tropospheric methane (CH 4 ) in the plume was investigated. CH 4 lifetimes between 14 h (at 1 ppb O 3 ) and 47 days (at 80 ppb O 3 ) were derived. While these lifetimes are considerably shorter than the atmospheric lifetime of CH 4 , the impact of gaseous chlorine on the CH 4 budget in the plume environment should nevertheless be relatively small due to plume dispersion (decreasing Cl concentrations) and ongoing mixing of the plume with the surrounding atmosphere (replenishing O 3 and CH 4 ).Published by Copernicus Publications on behalf of the European Geosciences Union. J. Gliß et al.: OClO and BrO observations in the volcanic plume of Mt. EtnaIn addition, all spectra were analysed...

Abstract. Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Abstract. This study presents a multiparameter analysis of aerosol trends over the last 2 decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical-composition and mass aerosol properties by using the observations from several ground-based networks. From these regional time series the aerosol trends have been derived for the different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases in aerosol optical depth (AOD) are found in Europe, North America, South America, North Africa and Asia, ranging from −1.2 % yr−1 to −3.1 % yr−1. An error and representativity analysis of the spatially and temporally limited observational data has been performed using model data subsets in order to investigate how much the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of 10 models (6 AeroCom phase III models and 4 CMIP6 models) and the CAMS reanalysis dataset and of their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, the column Ångström exponent, sulfate and particulate matter well (except in North Africa), but they show larger discrepancies for coarse-mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from that depicted by solely relying on ground-based observations. Using a model with complete diagnostics (NorESM2), we find a global increase in AOD of about 0.2 % yr−1 between 2000 and 2014, primarily caused by an increase in the loads of organic aerosols, sulfate and black carbon.

Abstract. Aerosol induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of such absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA) and mineral dust are diversely quantified in global climate models. As part of the third phase of the AeroCom model intercomparison initiative (AeroCom Phase III) we here document the distribution and magnitude of aerosol absorption in current global aerosols models and quantify the sources of intermodel spread. 15 models have provided total present-day absorption at 550 nm, and 11 of these models have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0056 [0.0020 to 0.0097] (550 nm) with range given as the minimum and maximum model values. This is 31 % higher compared to 0.0042 [0.0021 to 0.0076] in AeroCom Phase II, but the difference/increase is within one standard deviation which in this study is 0.0024 (0.0019 in Phase II). The models show considerable diversity in absorption. Of the summed component AAOD, 57 % (range 34–84 %) is estimated to be due to BC, 30 % (12–49 %) is due to dust and 14 % (4–49 %) is due to OA, however the components are not entirely independent. Models with the lowest BC absorption tend to have the highest OA absorption, which illustrates the complexities in separating the species. The geographical distribution of AAOD between the models varies greatly and reflects the spread in global mean AAOD and in the relative contributions from individual species. The optical properties of BC are recognized as a large source of uncertainty. The model mean BC mass absorption coefficient (MACBC) value is 9.8 [3.1 to 16.6] m2 g−1 (550 nm). Observed MAC values from various locations range between 5.7–20.0 m2 g−1 (550 nm). Compared to retrievals of AAOD and absorption Ångstrøm exponent (AAE) from ground-based observations from the Aerosol Robotic Network (AERONET) stations, most models underestimate total AAOD and AAE. The difference in spectral dependency between the models is striking.

Abstract. Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.

Ultraviolet (UV) SO 2 cameras have become a common tool to measure and monitor SO 2 emission rates, mostly from volcanoes but also from anthropogenic sources (e.g., power plants or ships). Over the past decade, the analysis of UV SO 2 camera data has seen many improvements. As a result, for many of the required analysis steps, several alternatives exist today (e.g., cell vs. DOAS based camera calibration; optical flow vs. cross-correlation based gas-velocity retrieval). This inspired the development of Pyplis (Python plume imaging software), an open-source software toolbox written in Python 2.7, which unifies the most prevalent methods from literature within a single, cross-platform analysis framework. Pyplis comprises a vast collection of algorithms relevant for the analysis of UV SO 2 camera data. These include several routines to retrieve plume background radiances as well as routines for cell and DOAS based camera calibration. The latter includes two independent methods to identify the DOAS field-of-view (FOV) within the camera images (based on (1) Pearson correlation and (2) IFR inversion method). Plume velocities can be retrieved using an optical flow algorithm as well as signal cross-correlation. Furthermore, Pyplis includes a routine to perform a first order correction of the signal dilution effect (also referred to as light dilution). All required geometrical calculations are performed within a 3D model environment allowing for distance retrievals to plume and local terrain features on a pixel basis. SO 2 emission rates can be retrieved simultaneously for an arbitrary number of plume intersections. Hence, Pyplis provides a state-of-the-art framework for more efficient and flexible analyses of UV SO 2 camera data and, therefore, marks an important step forward towards more transparency, reliability and inter-comparability of the results. Pyplis has been extensively and successfully tested using data from several field campaigns. Here, the main features are introduced using a dataset obtained at Mt. Etna, Italy on 16 September 2015.

&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art ESMs. Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) as well as space based observations from AATSR-SU instruments. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites.&lt;/p&gt; &lt;p&gt;Statistics are based mainly on normalised mean biases and Pearson correlation coefficients from colocated model and observation data in monthly resolution. Hence, the results are mostly representative for the regions covered by each of the observation networks. Model biases established against satellite data yield insights into remote continental areas and oceans, where ground-based networks lack site coverage. The satellite data themselves are evaluated against AERONET observations, to test our aggregation and re-gridding routines, suggesting relative AOD biases of &amp;#8722;5&amp;#8201;%, &amp;#8722;6&amp;#8201;%, +9&amp;#8201;% and +18&amp;#8201;% for AATSR-SU, MERGED-FMI, MODIS-aqua and MODIS-terra, respectively, with high correlations exceeding 0.8. Biases of fine and coarse AOD and AE in AATSR are found to be +2&amp;#8201;%, &amp;#8722;16&amp;#8201;% and +14.7&amp;#8201;% respectively, at AERONET sites, with correlations of the order of 0.8.&lt;/p&gt; &lt;p&gt;The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21&amp;#8201;%&amp;#8201;&amp;#177;&amp;#8201;17&amp;#8201;%. Against satellite data, the model AOD biases range from &amp;#8722;38&amp;#8201;% (MODIS-terra) to &amp;#8722;17&amp;#8201;% (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8&amp;#8211;0.9) and slightly lower against the two MODIS data-sets (0.6&amp;#8211;0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of &amp;#8722;10%&amp;#8201;&amp;#177;&amp;#8201;20&amp;#8201;% and &amp;#8722;41&amp;#8201;%&amp;#8201;&amp;#177;&amp;#8201;29&amp;#8201;% against AERONET and &amp;#8722;13&amp;#8201;% and &amp;#8722;24&amp;#8201;% against AATSR-SU, respectively. The differences in bias against AERONET and AATSR-SU are in agreement with the established satellite bias against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations.&lt;/p&gt; &lt;p&gt;Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of &amp;#8722;44&amp;#8201;%&amp;#8201;&amp;#177;&amp;#8201;22&amp;#8201;% and &amp;#8722;32&amp;#8201;%&amp;#8201;&amp;#177;&amp;#8201;34&amp;#8201;% for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. Broadly consistent negative bias in AOD and scattering suggest a general underestimate in aerosol effects in current global aerosol models.&lt;/p&gt; &lt;p&gt;The large diversity in the surface absorption results suggests differences in the model treatment of light absorption by black carbon (BC), dust (DU) and to a minor degree, organic aerosol (OA). Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models.&lt;/p&gt; &lt;p&gt;Evaluation of modelled column AEs shows an underestimation of 9&amp;#8201;%&amp;#8201;&amp;#177;&amp;#8201;24&amp;#8201;% against AERONET and &amp;#8722;21&amp;#8201;% against AATSR-SU. This suggests that overall, models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations.&lt;/p&gt; &lt;p&gt;An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. These are discussed in detail for each model individually. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.&lt;/p&gt;