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The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2) and shares with CESM2 the computer code infrastructure and many Earth system model components. However, NorESM2 employs entirely different ocean and ocean biogeochemistry models. The atmosphere component of NorESM2 (CAM-Nor) includes a different module for aerosol physics and chemistry, including interactions with cloud and radiation; additionally, CAM-Nor includes improvements in the formulation of local dry and moist energy conservation, in local and global angular momentum conservation, and in the computations for deep convection and air–sea fluxes. The surface components of NorESM2 have minor changes in the albedo calculations and to land and sea-ice models. We present results from simulations with NorESM2 that were carried out for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Two versions of the model are used: one with lower (∼ 2∘) atmosphere–land resolution and one with medium (∼ 1∘) atmosphere–land resolution. The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2 are assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. Compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 appears less sensitive to greenhouse gas forcing than its predecessors, with an estimated equilibrium climate sensitivity of 2.5 K in both resolutions on a 150-year time frame; however, this estimate increases with the time window and the climate sensitivity at equilibration is much higher. We also consider the model response to future scenarios as defined by selected Shared Socioeconomic Pathways (SSPs) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM-MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactory evolution of recent sea-ice area. In NorESM2-LM, an ice-free Arctic Ocean is only avoided in the SSP1-2.6 scenario.

The second version of the fully coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2), but has entirely different ocean and ocean biogeochemistry models; a new module for aerosols in the atmosphere model along with aerosol-radiation-cloud interactions and changes related to the moist energy formulation, deep convection scheme and angular momentum conservation; modified albedo and air-sea turbulent flux calculations; and minor changes to land and sea ice models. We show results from low (∼2°) and medium (∼1°) atmosphere-land resolution versions of NorESM2 that have both been used to carry out simulations for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2 is assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. As compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 is less sensitive to greenhouse gas forcing than its predecessors, with an equilibrium climate sensitivity of 2.5 K in both resolutions on a 150 year frame. We also consider the model response to future scenarios as defined by selected shared socioeconomic pathways (SSP) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM–MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactorily evolution of recent sea ice area. In NorESM2-LM an ice free Arctic Ocean is only avoided in the SSP1-2.6 scenario.

A total of sixteen global chemistry transport models and general circulation models have participated in this study. Fourteen models have been evaluated with regard to their ability to reproduce near-surface observed number concentration of aerosol particle and cloud condensation nuclei (CCN), and derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations, located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments, and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters > 50 nm and > 120 nm and −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. Fifteen models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −17 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally-derived value at lower than at higher updraft velocities (index-of-agreement of 0.47 vs 0.50). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration and to updraft velocity. Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high.

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters >50 and >120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations ( %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

Considering the ambitious climate targets of the Paris Agreement to limit global warming to 2°C, with aspirations of even 1.5°C, questions arise on how to achieve this. Climate geoengineering has been proposed as a potential tool to minimize global harm from anthropogenic climate change. Here, an Earth system model is used to evaluate the climate response when transferring from a high CO2 forcing scenario, RCP8.5, to a middle-of-the-road forcing scenario, like RCP4.5, using aerosol geoengineering. Three different techniques are considered: stratospheric aerosol injections (SAI), marine sky brightening (MSB), and cirrus cloud thinning (CCT). The climate states appearing in the climate geoengineering cases are found to be closer to RCP4.5 than RCP8.5 and many anthropogenic global warming symptoms are alleviated. All three techniques result in comparable global mean temperature evolutions. However, there are some notable differences in other climate variables due to the nature of the forcings applied. CCT acts mainly on the longwave part of the radiation budget, as opposed to MSB and SAI acting in the shortwave. This yields a difference in the response, particularly in the hydrological cycle. The responses in sea ice, sea level, ocean heat, and circulation, as well as the carbon cycle, are furthermore compared. Sudden termination of the aerosol injection geoengineering shows that the climate very rapidly (within two decades) reverts to the path of RCP8.5, questioning the sustainable nature of such climate geoengineering, and simultaneous mitigation during any such form of climate geoengineering would be needed to limit termination risks. © 2018 American Meteorological Society. Locked until 11.1.2019 due to copyright restrictions.

Desert dust plays an important role in the climate system through its impact on Earth¿s radiative budget and its role in the biogeochemical cycle as a source of iron in highnutrient- low-chlorophyll regions. A large degree of diversity exists between the many global models that simulate the dust cycle to estimate its impact on climate. We present the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations focusing on variables responsible for the uncertainties in estimating the direct radiative effect and the dust impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposi10 tion. Additional comparisons to Angstro¨m Exponent (AE), coarse mode AOD and dust surface concentration are included to extend the assessment of model performance. These datasets form a benchmark data set which is proposed for model inspection and future dust model developments. In general, models perform better in simulating climatology of vertically averaged integrated parameters (AOD and AE) in dusty sites 15 than they do with total deposition and surface concentration. Almost all models overestimate deposition fluxes over Europe, the Indian Ocean, the Atlantic Ocean and ice core data. Differences among the models arise when simulating deposition at remote sites with low fluxes over the Pacific and the Southern Atlantic Ocean. This study also highlights important differences in models ability to reproduce the deposition flux over Antarctica. The cause of this discrepancy could not be identified but different dust regimes at each site and issues with data quality should be considered. Models generally simulate better surface concentration at stations downwind of the main sources than at remote ones. Likewise, they simulate better surface concentration at stations affected by Saharan dust than at stations affected by Asian dust. Most models simulate the gradient in AOD and AE between the different dusty regions, however the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models also reproduce the dust transport across the Atlantic in terms of both AOD and AE; they simulate the offshore transport of West Africa throughout the year and limit the transport across the Atlantic to the summer months, yet overestimating the AOD and transporting too fine particles. However, most of the models do not reproduce the southward displacement of the dust cloud during the winter responsible of the transport of dust into South America. Based on the dependency of AOD on aerosol 5 burden and size distribution we use model data bias with respect to AOD and AE and infer on the over/under estimation of the dust emissions. According to this we suggest the emissions in the Sahara be between 792 and 2271 Tg/yr and the one in the Middle East between 376 and 526 Tg/yr., JRC.DDG.H.2-Climate change and air quality

Interest in the potential formation of secondary organic aerosol (SOA) through reactions of organic compounds in condensed aqueous phases is growing. In this study, the potential formation of SOA from irreversible aqueous-phase reactions of organic species in clouds was investigated. A new proposed aqueous-phase chemistry mechanism (AqChem) is coupled with the existing gas-phase Caltech Atmospheric Chemistry Mechanism (CACM) and the Model to Predict the Multiphase Partitioning of Organics (MPMPO) that simulate SOA formation. AqChem treats irreversible organic reactions that lead mainly to the formation of carboxylic acids, which are usually less volatile than the corresponding aldehydic compounds. Zero-dimensional model simulations were performed for tropospheric conditions with clouds present for three consecutive hours per day. Zero-dimensional model simulations show that 48-h average SOA formation is increased by 27% for a rural scenario with strong monoterpene emissions and 7% for an urban scenario with strong emissions of aromatic compounds, respectively, when irreversible organic reactions in clouds are considered. AqChem was also incorporated into the Community Multiscale Air Quality Model (CMAQ) version 4.4 with CACM/MPMPO and applied to a previously studied photochemical episode (3–4 August 2004) focusing on the eastern United States. The CMAQ study indicates that the maximum contribution of SOA formation from irreversible reactions of organics in clouds is 0.28 μg m−3 for 24-h average concentrations and 0.60 μg m−3 for one-hour average concentrations at certain locations. On average, domain-wide surface SOA predictions for the episode are increased by 9% when irreversible, in-cloud processing of organics is considered. Because aldehydes of carbon number greater than four are assumed to convert fully to the corresponding carboxylic acids upon reaction with OH in cloud droplets and this assumption may overestimate carboxylic acid formation from this reaction route, the present study provides an upper bound estimate of SOA formation via this pathway.

A global three-dimensional chemical transport model (CTM) is used to model the yearly cycle of sea salt. Sea salt particles are produced by wind acting on the sea surface, and they are removed by wet and dry deposition. In this study, forecast meteorological data are taken from the ECMWF. The modeled concentrations are compared to measured concentrations at sea level, and both absolute values and monthly variations compare well with measurements. Radiation calculations have been performed using the same meteorological input data as the CTM calculations. The global, yearly average burden of sea salt is found to be 12 mg m22. This is within the range of earlier estimates that vary between 11 and 22 mg m22. The radiative impact of sea salt is calculated to be 2 1.1 Wm 22. The total, yearly flux of sea salt is estimated to be 6500 Tg yr 21.

A global aerosol transport model (Oslo CTM2) with main aerosol components included is compared to five satellite retrievals of aerosol optical depth (AOD) and one data set of the satellite-derived radiative effect of aerosols. The model is driven with meteorological data for the period November 1996 to June 1997 which is the time period investigated in this study. The modelled AOD is within the range of the AOD from the various satellite retrievals over oceanic regions. The direct radiative effect of the aerosols as well as the atmospheric absorption by aerosols are in both cases found to be of the order of 20 Wm-2 in certain regions in both the satellite-derived and the modelled estimates as a mean over the period studied. Satellite and model data exhibit similar patterns of aerosol optical depth, radiative effect of aerosols, and atmospheric absorption of the aerosols. Recently published results show that global aerosol models have a tendency to underestimate the magnitude of the clear-sky direct radiative effect of aerosols over ocean compared to satellite-derived estimates. However, this is only to a small extent the case with the Oslo CTM2. The global mean direct radiative effect of aerosols over ocean is modelled with the Oslo CTM2 to be –5.5 Wm-2 and the atmospheric aerosol absorption 1.5 Wm-2.DOI: 10.1111/j.1600-0889.2006.00226.x

The effects of unified aerosol sources on global aerosol fields simulated by different models are examined in this paper. We compare results from two AeroCom experiments, one with different (ExpA) and one with unified emissions, injection heights, and particle sizes at the source (ExpB). Surprisingly, harmonization of aerosol sources has only a small impact on the simulated inter-model diversity of the global aerosol burden, and consequently global optical properties, as the results are largely controlled by model-specific transport, removal, chemistry (leading to the formation of secondary aerosols) and parameterizations of aerosol microphysics (e.g., the split between deposition pathways) and to a lesser extent by the spatial and temporal distributions of the (precursor) emissions. The burdens of black carbon and especially sea salt become more coherent in ExpB only, because the large ExpA diversities for these two species were caused by a few outliers. The experiment also showed that despite prescribing emission fluxes and size distributions, ambiguities in the implementation in individual models can lead to substantial differences. These results indicate the need for a better understanding of aerosol life cycles at process level (including spatial dispersal and interaction with meteorological parameters) in order to obtain more reliable results from global aerosol simulations. This is particularly important as such model results are used to assess the consequences of specific air pollution abatement strategies.

Large volcanic eruptions have strong impacts on both atmospheric and ocean dynamics that can last for decades. Numerical models have attempted to reproduce the effects of major volcanic eruptions on climate; however, there are remarkable inter-model disagreements related to both short-term dynamical response to volcanic forcing and long-term oceanic evolution. The lack of robust simulated behaviour is related to various aspects from model formulation to simulated background internal variability to the eruption details. Here, we use the Norwegian Earth System Model version 1 to calculate interactively the volcanic aerosol loading resulting from SO 2 emissions of the second largest high-latitude volcanic eruption in historical time (the Laki eruption of 1783). We use two different approaches commonly used interchangeably in the literature to generate ensembles. The ensembles start from different background initial states, and we show that the two approaches are not identical on short-time scales (

[1] This paper describes the aerosol model Organic Inorganic Lognormal Aerosol Model including Secondary Organic Aerosol (ORILAM-SOA) which is an extension of the lognormal aerosol dynamics model ORILAM. ORILAM-SOA consists of the original aerosol dynamics routines, a photochemical scheme able to predict SOA precursors, and an equilibrium scheme able to predict partitioning of the precursors between the gas and aerosol phases. We show that ORILAM-SOA is computationally efficient enough to be run in three-dimensional (3-D) atmospheric models. ORILAM-SOA is based on existing models. We use a numerical reduction technique to reduce the Caltech Atmospheric Chemistry Mechanism (CACM) and a new, fast, convergent iteration technique to increase the speed of the Model to Predict the Multiphase Partitioning of Organics (MPMPO). We compare the ORILAM-SOA to its parent models in terms of gas concentrations, aerosol concentrations, and CPU time spent during the computations. For illustrative purposes we include a 3-D simulation of SOA over southern France.

A thermodynamical model for treatment of gas/aerosol partitioning of semi volatile inorganic aerosols has been implemented in a global chemistry and aerosol transport model (Oslo CTM2). The sulphur cycle and sea salt particles have been implemented earlier in the Oslo CTM2 and the focus of this study is on nitrate partitioning to the aerosol phase and if particulate nitrate is expected to form in fine or coarse mode aerosols. Modelling of the formation of fine mode nitrate particles is complicated since it depends on other aerosol components and aerosol precursors as well as meteorological condition. The surface concentrations from the model are compared to observed surface concentrations at around 20 sites around Europe for nitrate and ammonium. The agreement for nitrate is good but the modelled values are somewhat underestimated compared to observations at high concentrations, whereas for ammonium the agreement is very good. However, we underscore that such a comparison is not of large importance for the aerosol optical depth of particulate nitrate since the vertical profile of aerosol components and their precursors are so important. Fine mode nitrate formation depends on vertical profiles of both ammonia/ammonium and sulphate. The model results show that fine mode particulate nitrate play a non-negligible role in the total aerosol composition in certain industrialized regions and therefore have a significant local radiative forcing. On a global scale the aerosol optical depth of fine mode nitrate is relatively small due to limited availability of ammonia and loss to larger sea salt particles. Inclusion of sea salt in the calculations reduces the aerosol optical depth and burden of fine mode nitrate by 25% on a global scale but with large regional variations.

[1] Several studies have shown the importance of aerosols in the Earth's radiative balance. The radiative effect of dust has earlier been quantified in global and regional climate models. Fewer studies have included prediction of aerosols online in numerical weather prediction (NWP) models. Predicting climate effect of aerosols is different from including aerosols actively in weather prediction because climate models give average responses over long timescales, whereas the purpose of weather prediction models is to calculate the right weather on short timescales. In this paper, we run a mesoscale NWP with four different assumptions on dust aerosols: (1) no dust, (2) climatological data set for dust aerosols, (3) forecasted dust using the Dust Entrainment and Deposition model (DEAD) and (4) same as assumption 3 but with decreased single scattering albedo. We show that the assumption on dust is important for predicting ground temperature and convective precipitation in the model. Dust changes the model physics through changing the radiative fluxes. We interpret the changes through analyzing the energy budgets for four zones close to the major dust sources. The zones include both convective and nonconvective areas. In convective areas over ocean, dust can decrease convective activity. The vertical gradient of the aerosols and their single scattering albedo determine how efficient they are. Over land, dust also influences the surface energy budget so that decreased latent heat fluxes result if dust plumes pass over areas where water evaporates from the surface.

International audience; The AeroCom exercise diagnoses multi-component aerosol modules in global modeling. In an initial assessment simulated global distributions for mass and mid-visible aerosol optical thickness (aot) were compared among 20 different modules. Model diversity was also explored in the context of previous comparisons. For the component combined aot general agreement has improved for the annual global mean. At 0.11 to 0.14, simulated aot values are at the lower end of global averages suggested by remote sensing from ground (AERONET ca. 0.135) and space (satel-lite composite ca. 0.15). More detailed comparisons, however , reveal that larger differences in regional distribution and significant differences in compositional mixture remain. Of Correspondence to: S. Kinne (stefan.kinne@zmaw.de) particular concern are large model diversities for contributions by dust and carbonaceous aerosol, because they lead to significant uncertainty in aerosol absorption (aab). Since aot and aab, both, influence the aerosol impact on the radia-tive energy-balance, the aerosol (direct) forcing uncertainty in modeling is larger than differences in aot might suggest. New diagnostic approaches are proposed to trace model differences in terms of aerosol processing and transport: These include the prescription of common input (e.g. amount, size and injection of aerosol component emissions) and the use of observational capabilities from ground (e.g. measurements networks) or space (e.g. correlations between aerosol and clouds).

Global atmospheric dust is simulated using the Dust Entrainment and Deposition (DEAD) model in combination with the global-scale Oslo chemical transport model CTM2 using meteorological data for 1996. Dust sources are calculated using both mean wind speeds with model resolution T63 and subgrid wind speeds. Different data sets are used to describe soil erodibility. We explain how the different assumptions about dust production affect atmospheric dust burden and deposition. Some aspects of the annual dust cycle, such as the east Asian dust emissions, are largely dependent on the data used to determine soil erodibility. Other aspects, such as the timing of the maximum in the African plume at Northern Hemisphere summer, are well modeled with all data sets applied here. We show that the daily variation in optical depth at Cape Verde on the west coast of Africa is well simulated when we assume that erodibility is correlated with surface reflectivity from Moderate-Resolution Imaging Spetroradiometer (MODIS) satellite data. Using a subgrid probability density function of wind speed to drive the dust sources facilitates dust emissions in areas with low wind speeds. Dust concentrations in remote areas are sensitive to the parameterization of wet deposition. Our results point out the need for a detailed soil erodibility data set for global dust modeling, and they suggest that surface reflectivity is potentially valuable for producing or evaluating such data sets.

[1] Recent field observations demonstrate that a significant discrepancy exists between models and measurements of large dust aerosol particles at remote sites. We assess the fraction of this bias explained by assumptions involving four different dust production processes. These include dust source size distribution (constant or dynamically changing according to saltation and sandblasting theory), wind speed distributions (using mean wind or a probability density function (PDF)), parent soil aggregate size distribution, and the discretization (number of bins) in the dust size distribution. The Dust Entrainment and Deposition global model is used to simulate the measurements from the Puerto Rican Dust Experiment (PRIDE) (2000). Using wind speed PDFs from observed National Centers for Environmental Prediction winds results in small changes in downwind size distribution for the production which neglects sandblasting, but it results in significant changes when production includes sandblasting. Saltation-sandblasting generally produces more large dust particles than schemes which neglect sandblasting. Parent soil aggregate size distribution is an important factor when calculating size-distributed dust emissions. Changing from a soil with large grains to a soil with smaller grains increases by 50% the fraction of large aerosols (D >5 μm) modeled at Puerto Rico. Assuming that the coarse medium sand typical of West Africa dominates all source regions produces the best agreement with PRIDE observations.

[1] The Oslo chemical transport model (Oslo CTM2) is driven by meteorological data to model mineral dust during the Saharan Dust Experiment (SHADE) campaign in September 2000. Model calculations of the optical properties and radiative transfer codes are used to assess the direct radiative impact in the solar and terrestrial regions of the spectrum. The model calculations are compared to a wide range of measurements (satellite, ground-based, and aircraft) during the campaign. The model reproduces the main features during the SHADE campaign, including a large mineral dust storm. The optical properties and the vertical profiles are in reasonable agreement with the measurements. There is a very good agreement between the modeled radiative impact and observations. The strongest local solar radiative impact we model is around −115 Wm−2. On a global scale the radiative effect of mineral dust from Sahara exerts a significant negative net radiative effect.

A global aerosol transport model (Oslo CTM2) with main aerosol components included is compared to five satellite retrievals of aerosol optical depth (AOD) and one data set of the satellite-derived radiative effect of aerosols. The model is driven with meteorological data for the period November 1996 to June 1997 which is the time period investigated in this study. The modelled AOD is within the range of the AOD from the various satellite retrievals over oceanic regions. The direct radiative effect of the aerosols as well as the atmospheric absorption by aerosols are in both cases found to be of the order of 20 Wm -2 in certain regions in both the satellite-derived and the modelled estimates as a mean over the period studied. Satellite and model data exhibit similar patterns of aerosol optical depth, radiative effect of aerosols, and atmospheric absorption of the aerosols. Recently published results show that global aerosol models have a tendency to underestimate the magnitude of the clear-sky direct radiative effect of aerosols over ocean compared to satellite-derived estimates. However, this is only to a small extent the case with the Oslo CTM2. The global mean direct radiative effect of aerosols over ocean is modelled with the Oslo CTM2 to be –5.5 Wm -2 and the atmospheric aerosol absorption 1.5 Wm -2 . DOI: 10.1111/j.1600-0889.2006.00226.x

The dominant process in producing fine dust aerosols during saltation is thought to be sandblasting. Recent studies claim that due to competing physical processes, emission efficiencies of dust aerosols oscillate with increasing wind friction speed. These oscillations can result in order of magnitude changes in dust mass emissions. Our work shows that emission efficiencies, and hence emissions of dust aerosols are smooth functions of the wind friction speed for natural soil size distributions. This rules out oscillations as an explanation for scatter in experimental data. We show and explain the reasons for the oscillations.

International audience; Simulation results of global aerosol models have been assembled in the framework of the AeroCom intercomparison exercise. In this paper, we analyze the life cycles of dust, sea salt, sulfate, black carbon and particulate organic matter as simulated by sixteen global aerosol models. The differences among the results (model diversities) for sources and sinks, burdens, particle sizes, water uptakes, and spatial dispersals have been established. These diversities have large consequences for the calculated radiative forcing and the aerosol concentrations at the surface. Processes and parameters are identified which deserve further research. The AeroCom all-models-average emissions are dominated by the mass of sea salt (SS), followed by dust (DU), sulfate (SO4), particulate organic matter (POM), and finally black carbon (BC). Interactive parameterizations of the emissions and contrasting particles sizes of SS and DU lead generally to higher diversities of these species, and for total aerosol. The lower diversity of the emissions of the fine aerosols, BC, POM, and SO4, is due to the use of similar emission inventories, and does therefore not necessarily indicate a better understanding of their sources. The diversity of SO4-sources is mainly caused by the disagreement on depositional loss of precursor gases and on chemical production. The diversities of the emissions are passed on to the burdens, but the latter are also strongly affected by the model-specific treatments of transport and aerosol processes. The burdens of dry masses decrease from largest to smallest: DU, SS, SO4, POM, and BC. The all-models-average residence time is shortest for SS with about half a day, followed by SO4 and DU with four days, and POM and BC with six and seven days, respectively. The wet deposition rate is controlled by the solubility and increases from DU, BC, POM to SO4 and SS. It is the dominant sink for SO4, BC, and POM, and contributes about one third to the total removal of SS and DU species. For SS and DU we find high diversities for the removal rate coefficients and deposition pathways. Models do neither agree on the split between wet and dry deposition, nor on that between sedimentation and other dry deposition processes. We diagnose an extremely high diversity for the uptake of ambient water vapor that influences the particle size and thus the sink rate coefficients. Furthermore, we find little agreement among the model results for the partitioning of wet removal into scavenging by convective and stratiform rain. Large differences exist for aerosol dispersal both in the vertical and in the horizontal direction. In some models, a minimum of total aerosol concentration is simulated at the surface. Aerosol dispersal is most pronounced for SO4 and BC and lowest for SS. Diversities are higher for meridional than for vertical dispersal, they are similar for the individual species and highest for SS and DU. For these two components we do not find a correlation between vertical and meridional aerosol dispersal. In addition the degree of dispersals of SS and DU is not related to their residence times. SO4, BC, and POM, however, show increased meridional dispersal in models with larger vertical dispersal, and dispersal is larger for longer simulated residence times.