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We evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher-order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework, referred as the “super-parameterization” (SP) with two different microphysics configurations to investigate their influences on rainfall simulations over Southern Amazonia. The two different microphysics configurations in SP are the one-moment cloud microphysics without aerosol treatment (SP1) and two-moment cloud microphysics coupled with aerosol treatment (SP2). Results show that both SP2 and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season, and reduce low biases of humidity in the lower troposphere with further reduced shallow clouds and increased surface solar flux. These changes increase moist static energy in the lower atmosphere, contribute to stronger convection and more rainfall. SP2 appears to realistically capture the observed increase of relative humidity prior to deep convection and it significantly increases rainfall in the afternoon; CLUBB significantly delays the afternoon peak rainfall and produces more precipitation in the early morning, due to more gradual transition between shallow and deep convection. In CAM5 and CAM5 with CLUBB, occurrence of more deep convection appears to be a result of stronger heating rather than higher relative humidity.

We used two 150-year pre-industrial simulations of the Community Earth System Model (CESM), one with interactive dust and the other with prescribed dust, to quantify the impacts of changes in wind during East Asian Winter Monsoon (EAWM) season on dust emissions, and the resulting consequences for interannual variations of temperature and precipitation over East Asia. The simulated December-January-February dust column burden and dust optical depth are lower over northern China in the strongest EAWM years than those of the weakest years by 38.3% and 37.2%, respectively. The decrease in dust over the dust source regions and the downwind region leads to an increase in direct radiative forcing (RF) at the surface by up to 1.5 Wm-2. The effects of EAWM-related variations in surface winds, precipitation and their effects on dust emissions and wet removal contribute 67% to the total dust-induced variations of direct RF at the surface and partly offset the cooling that occurs with the EAWM strengthening by heating the surface. The variations of surface air temperature induced by the changes in wind and dust emissions between the strongest and weakest EAWM years (strongest minus weakest) decrease by 0.4-0.6 K from eastern coastal China to Japan, which weakens the impact of EAWM on surface air temperature by 3–18% in these regions. The warming results from the combined effects of changes in direct RF, turbulent heat flux at the surface, and northwesterly wind anomalies that bring cold and dry air from Siberia to these regions. Over eastern coastal China, the variations of large-scale precipitation induced by the feedback of EAWM-related changes in wind on dust emissions decrease by 10-30% in winter because of the reducing changes in surface air temperature and the anomalous circulation.

We use 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of the East Asian Monsoon strength on interannual variations of springtime dust concentrations over China. The simulated interannual variations in March-April-May (MAM) dust column concentrations range between 20–40% and 10–60% over eastern and western China, respectively. The dust concentrations over eastern China correlate negatively with the East Asian Monsoon (EAM) index, which represents the strength of monsoon, with a regionally averaged correlation coefficient of −0.64. Relative to the strongest EAM years, MAM dust concentrations in the weakest EAM years are higher over China, with regional relative differences of 55.6%, 29.6%, and 13.9% in the run with emissions calculated interactively and of 33.8%, 10.3%, and 8.2% over eastern, central, and western China, respectively, in the run with prescribed emissions. Both interactive run and prescribed emission run show the similar pattern of climate change between the weakest and strongest EAM years. Strong anomalous northwesterly and westerly winds over the Gobi and Taklamakan deserts during the weakest EAM years result in larger transport fluxes, and thereby increase the dust concentrations over China. These differences in dust concentrations between the weakest and strongest EAM years (weakest-strongest) lead to the change in the net radiative forcing by up to −8 and −3 W m−2 at the surface, compared to −2.4 and +1.2 W m−2 at the top of the atmosphere over eastern and western China, respectively.

The ability of 11 models in simulating the aerosol vertical distribution from regional to global scales, as part of the second phase of the AeroCom model intercomparison initiative (AeroCom II), is assessed and compared to results of the first phase. The evaluation is performed using a global monthly gridded data set of aerosol extinction profiles built for this purpose from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Layer Product 3.01. Results over 12 subcontinental regions show that five models improved, whereas three degraded in reproducing the interregional variability in Zα0–6 km, the mean extinction height diagnostic, as computed from the CALIOP aerosol profiles over the 0–6 km altitude range for each studied region and season. While the models' performance remains highly variable, the simulation of the timing of the Zα0–6 km peak season has also improved for all but two models from AeroCom Phase I to Phase II. The biases in Zα0–6 km are smaller in all regions except Central Atlantic, East Asia, and North and South Africa. Most of the models now underestimate Zα0–6 km over land, notably in the dust and biomass burning regions in Asia and Africa. At global scale, the AeroCom II models better reproduce the Zα0–6 km latitudinal variability over ocean than over land. Hypotheses for the performance and evolution of the individual models and for the intermodel diversity are discussed. We also provide an analysis of the CALIOP limitations and uncertainties contributing to the differences between the simulations and observations.

PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE 10.1002/2015JD024503 Key Points: • Interannual variability in cloud radiative effects is driven by midlevel and high clouds • Wind-related feedbacks on natural aerosol emissions enhance this variability by 3 to 5% • Variations in natural aerosol concentrations enhance interannual variability by 1 to 3% Supporting Information: • Supporting Information S1 Correspondence to: L. M. Russell, lmrussell@ucsd.edu Citation: Yang, Y., et al. (2016), Impacts of ENSO events on cloud radiative effects in preindustrial conditions: Changes in cloud fraction and their dependence on interactive aerosol emissions and concentrations, J. Geophys. Res. Atmos., 121, 6321–6335, doi:10.1002/ 2015JD024503. Received 13 NOV 2015 Accepted 16 MAY 2016 Accepted article online 19 MAY 2016 Published online 2 JUN 2016 Impacts of ENSO events on cloud radiative effects in preindustrial conditions: Changes in cloud fraction and their dependence on interactive aerosol emissions and concentrations Yang Yang 1,2 , Lynn M. Russell 1 , Li Xu 1 , Sijia Lou 1 , Maryam A. Lamjiri 1 , Richard C. J. Somerville 1 , Arthur J. Miller 1 , Daniel R. Cayan 1 , Michael J. DeFlorio 1 , Steven J. Ghan 3 , Ying Liu 3 , Balwinder Singh 3 , Hailong Wang 3 , Jin-Ho Yoon 4 , and Philip J. Rasch 3 Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA, 2 Now at Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA, 3 Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA, 4 Gwangju Institute of Science and Technology, Gwangju, South Korea Abstract We use three 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of El Nino–Southern Oscillation (ENSO) events on shortwave and longwave cloud radiative effects (CRE SW and CRE LW ). Compared to recent observations from the Clouds and the Earth’s Radiant Energy System data set, the model simulation successfully reproduces larger variations of CRE SW and CRE LW over the tropics. The ENSO cycle is found to dominate interannual variations of cloud radiative effects. Simulated cooling (warming) effects from CRE SW (CRE LW ) are strongest over the tropical western and central Pacific Ocean during warm ENSO events, with the largest difference between 20 and 60 W m 2 , with weaker effects of 10–40 W m 2 over Indonesian regions and the subtropical Pacific Ocean. Sensitivity tests show that variations of cloud radiative effects are mainly driven by ENSO-related changes in cloud fraction. The variations in midlevel and high cloud fractions each account for approximately 20–50% of the interannual variations of CRE SW over the tropics and almost all of the variations of CRE LW between 60°S and 60°N. The variation of low cloud fraction contributes to most of the variations of CRE SW over the midlatitude oceans. Variations in natural aerosol concentrations explained 10–30% of the variations of both CRE SW and CRE LW over the tropical Pacific, Indonesian regions, and the tropical Indian Ocean. Changes in natural aerosol emissions and concentrations enhance 3–5% and 1–3% of the variations of cloud radiative effects averaged over the tropics. 1. Introduction Clouds strongly influence the Earth’s radiation balance. They reflect incoming solar radiation back to space, which enhances the reflected solar flux by 47.5 ± 3 W m 2 globally, and absorb outgoing infrared radiation, which reduces the outgoing longwave flux relative to clear sky by approximately 26.4 ± 4 W m 2 . Overall, clouds exert a net cooling effect of about 21.1 ± 5 W m 2 at the top of atmosphere (TOA) [Stephens et al., 2012], which is 6 times larger than that from doubling CO 2 concentration [Ramanathan et al., 1989; Loeb et al., 2009]. Any changes in cloud properties such as cloud fraction, cloud top height, and microphysical fea- tures would perturb cloud radiative forcing and greatly modulate the radiative balance of the Earth system [Slingo, 1990; Wielicki et al., 1998; Curry et al., 2000; Stephens, 2005]. The Intergovernmental Panel on Climate Change reported that simulations of clouds and their radiative feedbacks are still one of the largest uncertainties in the fifth-generation climate models [Boucher et al., 2013]. ©2016. American Geophysical Union. All Rights Reserved. YANG ET AL. On interannual time scales, many regional changes in the global climate system are associated with the El Nino–Southern Oscillation (ENSO). ENSO is characterized by anomalous sea surface temperatures (SSTs) in the equatorial Pacific and has far-reaching impacts on global and regional temperature, precipitation, and circulation. Using cloud data from the Extended Edited Cloud Reports Archive (EECRA) from year 1954 to recent years, Park and Leovy [2004] and Eastman et al. [2011] both showed that interannual variations of cloud cover in the tropics have strong correlations to the ENSO index. For example, warmer central and eastern tropical Pacific SST (warm ENSO phase, i.e., El Nino) is associated with increased cloud cover in the tropical central Pacific Ocean and reduced cloud cover over the Indonesian and eastern Pacific regions, and vice versa for cool ENSO phase (La Nina) events. IMPACT OF ENSO ON CLOUD RADIATIVE EFFECT

Accurate representation of global stratospheric aerosols from volcanic and non-volcanic sulfur emissions is key to understanding the cooling effects and ozone-losses that may be linked to volcanic activity. Attribution of climate variability to volcanic activity is of particular interest in relation to the post-2000 slowing in the rate of global average temperature increases. We have compiled a database of volcanic SO2 emissions and plume altitudes for eruptions from 1990 to 2014, and developed a new prognostic capability for simulating stratospheric sulfate aerosols in the Community Earth System Model (CESM). We used these combined with other non-volcanic emissions of sulfur sources to reconstruct global aerosol properties from 1990 to 2014. Our calculations show remarkable agreement with ground-based lidar observations of stratospheric aerosol optical depth (SAOD), and with in situ measurements of stratospheric aerosol surface area density (SAD). These properties are key parameters in calculating the radiative and chemical effects of stratospheric aerosols. Our SAOD calculations represent a clear improvement over available satellite-based analyses, which generally ignore aerosol extinction below 15 km, a region that can contain the vast majority of stratospheric aerosol extinction at mid- and high-latitudes. Our SAD calculations greatly improve on that provided for the Chemistry-Climate Model Initiative, which misses about 60% of the SAD measured in situ on average during both volcanically active and volcanically quiescent periods.

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. In Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem, provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization schemes (CAM5–Base) and the other with the Cloud Layers Unified by Binormals scheme (CAM5–CLUBB). When comparing the direct model outputs, the authors find that CAM5–CLUBB produces more MBL clouds, a smoother transition from stratocumulus to cumulus, and a tighter correlation between in-cloud water and cloud fraction than CAM5–Base. In the model-to-observation comparison using the COSP satellite simulators, the authors find that both simulations capture the main features and spatial patterns of the observed cloud fraction from MODIS and shortwave cloud radiative forcing (SWCF) from CERES. However, CAM5–CLUBB suffers more than CAM5–Base from a problem that can be best summarized as “undetectable” clouds (i.e., a significant fraction of simulated MBL clouds are thinner than the MODIS detection threshold). This issue leads to a smaller COSP–MODIS cloud fraction and a weaker SWCF in CAM5–CLUBB than the observations and also CAM5–Base in the tropical descending regions. Finally, the authors compare modeled radar reflectivity with CloudSat observations and find that both simulations, especially CAM5–CLUBB, suffer from an excessive drizzle problem. Further analysis reveals that the subgrid precipitation enhancement factors in CAM5–CLUBB are unrealistically large, which makes MBL clouds precipitate too excessively, and in turn results in too many undetectable thin clouds.

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25°, with the meteorology nudged toward the Year Of Tropical Convection analysis, and cloud simulators and the collocated A-Train satellite observations are used to explore the resolution dependence of aerosol-cloud interactions. The higher-resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the Northern Hemisphere midlatitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m−2 (−30%) compared to the 2° model, leading to a 0.26 W m−2 reduction (−15%) in the global annual average AIF.

Dust variability in the climate system has been studied for several decades, yet there remains an incomplete understanding of the dynamical mechanisms controlling interannual and decadal variations in dust transport. The sparseness of multi-year observational datasets has limited our understanding of the relationship between climate variations and atmospheric dust. We use available in situ and satellite observations of dust and a century-length fully coupled Community Earth System Model (CESM) simulation to show that the El Nino-Southern Oscillation (ENSO) exerts a control on North African dust transport during boreal summer. In CESM, this relationship is stronger over the dusty tropical North Atlantic than near Barbados, one of the few sites having a multi-decadal observed record. During strong La Nina summers in CESM, a statistically significant increase in lower tropospheric easterly wind is associated with an increase in North African dust transport over the Atlantic. Barbados dust and Pacific SST variability are only weakly correlated in both observations and CESM, suggesting that other processes are controlling the cross-basin variability of dust. We also use our CESM simulation to show that the relationship between downstream North African dust transport and ENSO fluctuates on multidecadal timescales and is associated with a phase shift in the North Atlantic Oscillation. Our findings indicate that existing observations of dust over the tropical North Atlantic are not extensive enough to completely describe the variability of dust and dust transport, and demonstrate the importance of global models to supplement and interpret observational records.

Much of the uncertainty in estimates of the anthropogenic forcing of climate change comes from uncertainties in the instantaneous effect of aerosols on cloud albedo, known as the Twomey effect or the radiative forcing from aerosol–cloud interactions (RFaci), a component of the total or effective radiative forcing. Because aerosols serving as cloud condensation nuclei can have a strong influence on the cloud droplet number concentration (Nd), previous studies have used the sensitivity of the Nd to aerosol properties as a constraint on the strength of the RFaci. However, recent studies have suggested that relationships between aerosol and cloud properties in the present-day climate may not be suitable for determining the sensitivity of the Nd to anthropogenic aerosol perturbations. Using an ensemble of global aerosol–climate models, this study demonstrates how joint histograms between Nd and aerosol properties can account for many of the issues raised by previous studies. It shows that if the anthropogenic contribution to the aerosol is known, the RFaci can be diagnosed to within 20% of its actual value. The accuracy of different aerosol proxies for diagnosing the RFaci is investigated, confirming that using the aerosol optical depth significantly underestimates the strength of the aerosol–cloud interactions in satellite data.

This study uses a century length preindustrial climate simulation by the Community Earth System Model (CESM 1.0) to explore statistical relationships between dust, clouds, and atmospheric circulation and to suggest a semidirect dynamical mechanism linking subtropical North Atlantic lower tropospheric cloud cover with North African dust transport. The length of the run allows us to account for interannual variability of North African dust emissions and transport in the model. CESM's monthly climatology of both aerosol optical depth and surface dust concentration at Cape Verde and Barbados, respectively, agree well with available observations, as does the aerosol size distribution at Cape Verde. In addition, CESM shows strong seasonal cycles of dust burden and lower tropospheric cloud fraction, with maximum values occurring during boreal summer, when a strong correlation between these two variables exists over the subtropical North Atlantic. Calculations of Estimated Inversion Strength (EIS) and composites of EIS on high and low downstream North African dust months during boreal summer reveal that dust is likely increasing inversion strength over this region due to both solar absorption and reflection. We find no evidence for a microphysical link between dust and lower tropospheric clouds in this region. These results yield new insight over an extensive period of time into the complex relationship between North African dust and North Atlantic lower tropospheric clouds, which has previously been hindered by spatiotemporal constraints of observations. Our findings lay a framework for future analyses using different climate models and submonthly data over regions with different underlying dynamics.

Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr−1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m−2 with 90% uncertainty bounds of (+0.08, +1.27) W m−2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m−2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m−2 with 90% uncertainty bounds of +0.17 to +2.1 W m−2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m−2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (−0.50 to +1.08) W m−2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (−0.06 W m−2 with 90% uncertainty bounds of −1.45 to +1.29 W m−2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

Many global aerosol and climate models, including the widely used Community Atmosphere Model version 5 (CAM5), have large biases in predicting aerosols in remote regions such as upper troposphere and high latitudes. In this study, we conduct CAM5 sensitivity simulations to understand the role of key processes associated with aerosol transformation and wet removal affecting the vertical and horizontal long-range transport of aerosols to the remote regions. Improvements are made to processes that are currently not well represented in CAM5, which are guided by surface and aircraft measurements together with results from a multi-scale aerosol-climate model (PNNL-MMF) that explicitly represents convection and aerosol-cloud interactions at cloud-resolving scales. We pay particular attention to black carbon (BC) due to its importance in the Earth system and the availability of measurements. We introduce into CAM5 a new unified scheme for convective transport and aerosol wet removal with explicit aerosol activation above convective cloud base. This new implementation reduces the excessive BC aloft to better simulate observed BC profiles that show decreasing mixing ratios in the mid- to upper-troposphere. After implementing this new unified convective scheme, we examine wet removal of submicron aerosols that occurs primarily through cloud processes. The wet removal depends strongly on the sub-grid scale liquid cloud fraction and the rate of conversion of liquid water to precipitation. These processes lead to very strong wet removal of BC and other aerosols over mid- to high latitudes during winter months. With our improvements, the Arctic BC burden has a10-fold (5-fold) increase in the winter (summer) months, resulting in a much better simulation of the BC seasonal cycle as well. Arctic sulphate and other aerosol species also increase but to a lesser extent. An explicit treatment of BC aging with slower aging assumptions produces an additional 30-fold (5-fold) increase in the Arctic winter (summer) BC burden. This BC aging treatment, however, has minimal effect on other under-predicted species. Interestingly, our modifications to CAM5 that aim at improving prediction of high-latitude and upper tropospheric aerosols also produce much better aerosol optical depth over various other regions globally when compared to multi-year AERONET retrievals. The improved aerosol distributions have impacts on other aspects of CAM5, improving the simulation of global mean liquid water path and cloud forcing.

A primary goal of the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100 climate change in the current generation of climate models. Here we evaluate historical and future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of which also participated in the Coupled Model Intercomparison Project phase 5 (CMIP5). The models generally reproduce present-day climatological total aerosol optical depth (AOD) relatively well. They have quite different contributions from various aerosol components to this total, however, and most appear to underestimate AOD over East Asia. The models generally capture 1980–2000 AOD trends fairly well, though they underpredict AOD increases over the Yellow/Eastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, South America and Southern Hemisphere Africa. We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing; AF, including direct and indirect effects). The models' calculated all aerosol all-sky 1850 to 2000 global mean annual average RF ranges from −0.06 to −0.49 W m−2, with a mean of −0.26 W m−2 and a median of −0.27 W m−2. Adjusting for missing aerosol components in some models brings the range to −0.12 to −0.62 W m−2, with a mean of −0.39 W m−2. Screening the models based on their ability to capture spatial patterns and magnitudes of AOD and AOD trends yields a quality-controlled mean of −0.42 W m−2 and range of −0.33 to −0.50 W m−2 (accounting for missing components). The CMIP5 subset of ACCMIP models spans −0.06 to −0.49 W m−2, suggesting some CMIP5 simulations likely have too little aerosol RF. A substantial, but not well quantified, contribution to historical aerosol RF may come from climate feedbacks (35 to −58 %). The mean aerosol AF during this period is −1.12 W m−2 (median value −1.16 W m−2, range −0.72 to −1.44 W m−2), indicating that adjustments to aerosols, which include cloud, water vapor and temperature, lead to stronger forcing than the aerosol direct RF. Both negative aerosol RF and AF are greatest over and near Europe, South and East Asia and North America during 1850 to 2000. AF, however, is positive over both polar regions, the Sahara, and the Karakoram. Annual average AF is stronger than 0.5 W m−2 over parts of the Arctic and more than 1.5 W m−2 during boreal summer. Examination of the regional pattern of RF and AF shows that the multi-model spread relative to the mean of AF is typically the same or smaller than that for RF over areas with substantial forcing. Historical aerosol RF peaks in nearly all models around 1980, declining thereafter. Aerosol RF declines greatly in most models over the 21st century and is only weakly sensitive to the particular Representative Concentration Pathway (RCP). One model, however, shows approximate stabilization at current RF levels under RCP 8.5, while two others show increasingly negative RF due to the influence of nitrate aerosols (which are not included in most models). Aerosol AF, in contrast, continues to become more negative during 1980 to 2000 despite the turnaround in RF. Total anthropogenic composition forcing (RF due to well-mixed greenhouse gases (WMGHGs) and ozone plus aerosol AF) shows substantial masking of greenhouse forcing by aerosols towards the end of the 20{th} century and in the early 21st century at the global scale. Regionally, net forcing is negative over most industrialized and biomass burning regions through 1980, but remains strongly negative only over East and Southeast Asia by 2000 and only over a very small part of Southeast Asia by 2030 (under RCP8.5). Net forcing is strongly positive by 1980 over the Sahara, Arabian peninsula, the Arctic, Southern Hemisphere South America, Australia and most of the oceans. Both the magnitude of and area covered by positive forcing expand steadily thereafter. There is no clear relationship between aerosol AF and climate sensitivity in the CMIP5 subset of ACCMIP models. There is a clear link between the strength of aerosol+ozone forcing and the global mean historical climate response to anthropogenic non-WMGHG forcing (ANWF). The models show ~20–35% greater climate sensitivity to ANWF than to WMGHG forcing, at least in part due to geographic differences in climate sensitivity. These lead to ~50% more warming in the Northern Hemisphere in response to increasing WMGHGs. This interhemispheric asymmetry is enhanced for ANWF by an additional 10–30%. At smaller spatial scales, response to ANWF and WMGHGs show distinct differences.

Two 150-yr preindustrial simulations with and without interactive sea salt emissions from the Community Earth System Model (CESM) are performed to quantify the interactions between sea salt emissions and El Niño–Southern Oscillation (ENSO). Variations in sea salt emissions over the tropical Pacific Ocean are affected by changing wind speed associated with ENSO variability. ENSO-induced interannual variations in sea salt emissions result in decreasing (increasing) aerosol optical depth (AOD) by 0.03 over the equatorial central-eastern (western) Pacific Ocean during El Niño events compared to those during La Niña events. These changes in AOD further increase (decrease) radiative fluxes into the atmosphere by +0.2 (−0.4) W m−2 over the tropical eastern (western) Pacific. Thereby, sea surface temperature increases (decreases) by 0.2–0.4 K over the tropical eastern (western) Pacific Ocean during El Niño compared to La Niña events and enhances ENSO variability by 10%. The increase in ENSO amplitude is a result of systematic heating (cooling) during the warm (cold) phase of ENSO in the eastern Pacific. Interannual variations in sea salt emissions then produce the anomalous ascent (subsidence) over the equatorial eastern (western) Pacific between El Niño and La Niña events, which is a result of heating anomalies. Owing to variations in sea salt emissions, the convective precipitation is enhanced by 0.6–1.2 mm day−1 over the tropical central-eastern Pacific Ocean and weakened by 0.9–1.5 mm day−1 over the Maritime Continent during El Niño compared to La Niña events, enhancing the precipitation variability over the tropical Pacific.

We examined the multi-year mean and variability of dimethyl sulfide (DMS) and its relationship to sulfate aerosols, as well as cloud microphysical and radiative properties. We conducted a 150-year simulation using pre-industrial conditions produced by the Community Earth System Model embedded with a dynamic DMS module. The model simulated the mean spatial distribution of DMS emissions and burden, as well as sulfur budgets associated with DMS, SO2, H2SO4, and sulfate that were generally similar to available observations and inventories for a variety of regions. Changes in simulated sea-to-air DMS emissions and associated atmospheric abundance, along with associated aerosols and cloud and radiative properties, were consistently dominated by the El Nino-Southern Oscillation (ENSO) cycle in the tropical Pacific region. Simulated DMS, aerosols, and clouds showed a weak positive feedback on sea surface temperature. This feedback suggests a link among DMS, aerosols, clouds, and climate on interannual timescales. The variability of DMS emissions associated with ENSO was primarily caused by a higher variation in wind speed during La Nina events. The simulation results also suggest that variations in DMS emissions increase the frequency of La Nina events but do not alter the ENSO variability in terms of the standard deviation of Nino 3 SST anomalies.

Cloud-system resolving simulations with the chemistry version of the Weather Research and Forecasting (WRF-Chem) model are used to quantify the relative impacts of regional anthropogenic and oceanic emissions on changes in aerosol properties, cloud macro- and microphysics, and cloud radiative forcing over the Southeast Pacific (SEP) during the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) (15 October–16 November 2008). Two distinct regions are identified. The near-coast polluted region is characterized by low surface precipitation rates, the strong suppression of non-sea-salt particle activation due to sea-salt particles, a predominant albedo effect in aerosol indirect effects, and limited impact of aerosols associated with anthropogenic emissions on clouds. Opposite sensitivities to natural marine and anthropogenic aerosol perturbations are seen in cloud properties (e.g., cloud optical depth and cloud-top and cloud-base heights), precipitation, and the top-of-atmosphere and surface shortwave fluxes over this region. The relatively clean remote region is characterized by large contributions of aerosols from non-regional sources (lateral boundaries) and much stronger drizzle at the surface. Under a scenario of five-fold increase in regional anthropogenic emissions, this relatively clean region shows large cloud responses, for example, a 13% increase in cloud-top height and a 9% increase in albedo in response to a moderate increase (25% of the reference case) in cloud condensation nuclei (CCN) concentration. The reduction of precipitation due to this increase in anthropogenic aerosols more than doubles the aerosol lifetime in the clean marine boundary layer. Therefore, the aerosol impacts on precipitation are amplified by the positive feedback of precipitation on aerosol, which ultimately alters the cloud micro- and macro-physical properties, leading to strong aerosol-cloud-precipitation interactions. The high sensitivity is also related to an increase in cloud-top entrainment rate (by 16% at night) due to the increased anthropogenic aerosols. The simulated aerosol-cloud-precipitation interactions due to the increased anthropogenic aerosols have a stronger diurnal cycle over the clean region compared to the near-coast region with stronger interactions at night. During the day, solar heating results in more frequent decoupling of the cloud and sub-cloud layers, thinner clouds, reduced precipitation, and reduced sensitivity to the increase in anthropogenic emissions. This study shows the importance of natural aerosols in accurately quantifying anthropogenic forcing within a regional modeling framework. The results of this study also imply that the energy balance perturbations from increased anthropogenic emissions are larger in the more susceptible clean environment than in already polluted environment and are larger than possible from the first indirect effect alone.

In the first part of this paper series (Meskhidze et al., 2011), a treatment of marine organic aerosols (including primary organic aerosol, secondary organic aerosols, and methane sulfonate) was implemented into the Community Atmosphere Model version 5 (CAM5) with a 7-mode Modal Aerosol Module. A series of simulations was conducted to quantify the changes in aerosol and cloud condensation nuclei concentrations in the marine boundary layer. In this study, changes in the cloud microphysical properties and radiative forcing resulting from marine organic aerosols are assessed. Model simulations show that the anthropogenic aerosol indirect forcing (AIF) predicted by CAM5 is decreased in absolute magnitude by up to ~0.10 W m−2 (8%) when marine organic aerosols are included. Changes in the AIF from marine organic aerosols are associated with small global increases in low-level in-cloud droplet number concentration and liquid water path of ~1.3 cm−3 (~1.6%) and 0.2 g m−2 (0.5%), respectively. Areas especially sensitive to changes in cloud properties due to marine organic aerosol include the Southern Ocean, North Pacific Ocean, and North Atlantic Ocean, all of which are characterized by high marine organic emission rates. As climate models are particularly sensitive to the background aerosol concentration, this small but non-negligible change in the AIF due to marine organic aerosols provides a notable link for ocean-ecosystem marine low-level cloud interactions and may be a candidate for consideration in future earth system models.

A modal aerosol module (MAM) has been developed for the Community Atmosphere Model version 5 (CAM5), the atmospheric component of the Community Earth System Model version 1 (CESM1). MAM is capable of simulating the aerosol size distribution and both internal and external mixing between aerosol components, treating numerous complicated aerosol processes and aerosol physical, chemical and optical properties in a physically-based manner. Two MAM versions were developed: a more complete version with seven lognormal modes (MAM7), and a version with three lognormal modes (MAM3) for the purpose of long-term (decades to centuries) simulations. In this paper a description and evaluation of the aerosol module and its two representations are provided. Sensitivity of the aerosol lifecycle to simplifications in the representation of aerosol is discussed. Simulated sulfate and secondary organic aerosol (SOA) mass concentrations are remarkably similar between MAM3 and MAM7. Differences in primary organic matter (POM) and black carbon (BC) concentrations between MAM3 and MAM7 are also small (mostly within 10%). The mineral dust global burden differs by 10% and sea salt burden by 30–40% between MAM3 and MAM7, mainly due to the different size ranges for dust and sea salt modes and different standard deviations of the log-normal size distribution for sea salt modes between MAM3 and MAM7. The model is able to qualitatively capture the observed geographical and temporal variations of aerosol mass and number concentrations, size distributions, and aerosol optical properties. However, there are noticeable biases; e.g., simulated BC concentrations are significantly lower than measurements in the Arctic. There is a low bias in modeled aerosol optical depth on the global scale, especially in the developing countries. These biases in aerosol simulations clearly indicate the need for improvements of aerosol processes (e.g., emission fluxes of anthropogenic aerosols and precursor gases in developing countries, boundary layer nucleation) and properties (e.g., primary aerosol emission size, POM hygroscopicity). In addition, the critical role of cloud properties (e.g., liquid water content, cloud fraction) responsible for the wet scavenging of aerosol is highlighted.

The authors have decomposed the anthropogenic aerosol radiative forcing into direct contributions from each aerosol species to the planetary energy balance through absorption and scattering of solar radiation, indirect effects of anthropogenic aerosol on solar and infrared radiation through droplet and crystal nucleation on aerosol, and semidirect effects through the influence of solar absorption on the distribution of clouds. A three-mode representation of the aerosol in version 5.1 of the Community Atmosphere Model (CAM5.1) yields global annual mean radiative forcing estimates for each of these forcing mechanisms that are within 0.1 W m−2 of estimates using a more complex seven-mode representation that distinguishes between fresh and aged black carbon and primary organic matter. Simulating fresh black carbon particles separately from internally mixed accumulation mode particles is found to be important only near fossil fuel sources. In addition to the usual large indirect effect on solar radiation, this study finds an unexpectedly large positive longwave indirect effect (because of enhanced cirrus produced by homogenous nucleation of ice crystals on anthropogenic sulfate), small shortwave and longwave semidirect effects, and a small direct effect (because of cancelation and interactions of direct effects of black carbon and sulfate). Differences between the three-mode and seven-mode versions are significantly larger (up to 0.2 W m−2) when the hygroscopicity of primary organic matter is decreased from 0.1 to 0 and transfer of the primary carbonaceous aerosol to the accumulation mode in the seven-mode version requires more hygroscopic material coating the primary particles. Radiative forcing by cloudborne anthropogenic black carbon is only −0.07 W m−2.

Marine organic aerosol emissions have been implemented and evaluated within the National Center of Atmospheric Research (NCAR)'s Community Atmosphere Model (CAM5) with the Pacific Northwest National Laboratory's 7-mode Modal Aerosol Module (MAM-7). Emissions of marine primary organic aerosols (POA), phytoplankton-produced isoprene- and monoterpenes-derived secondary organic aerosols (SOA) and methane sulfonate (MS−) are shown to affect surface concentrations of organic aerosols in remote marine regions. Global emissions of submicron marine POA is estimated to be 7.9 and 9.4 Tg yr−1, for the Gantt et al. (2011) and Vignati et al. (2010) emission parameterizations, respectively. Marine sources of SOA and particulate MS− (containing both sulfur and carbon atoms) contribute an additional 0.2 and 5.1 Tg yr−1, respectively. Widespread areas over productive waters of the Northern Atlantic, Northern Pacific, and the Southern Ocean show marine-source submicron organic aerosol surface concentrations of 100 ng m−3, with values up to 400 ng m−3 over biologically productive areas. Comparison of long-term surface observations of water insoluble organic matter (WIOM) with POA concentrations from the two emission parameterizations shows that despite revealed discrepancies (often more than a factor of 2), both Gantt et al. (2011) and Vignati et al. (2010) formulations are able to capture the magnitude of marine organic aerosol concentrations, with the Gantt et al. (2011) parameterization attaining better seasonality. Model simulations show that the mixing state of the marine POA can impact the surface number concentration of cloud condensation nuclei (CCN). The largest increases (up to 20%) in CCN (at a supersaturation (S) of 0.2%) number concentration are obtained over biologically productive ocean waters when marine organic aerosol is assumed to be externally mixed with sea-salt. Assuming marine organics are internally-mixed with sea-salt provides diverse results with increases and decreases in the concentration of CCN over different parts of the ocean. The sign of the CCN change due to the addition of marine organics to sea-salt aerosol is determined by the relative significance of the increase in mean modal diameter due to addition of mass, and the decrease in particle hygroscopicity due to compositional changes in marine aerosol. Based on emerging evidence for increased CCN concentration over biologically active surface ocean areas/periods, our study suggests that treatment of sea spray in global climate models (GCMs) as an internal mixture of marine organic aerosols and sea-salt will likely lead to an underestimation in CCN number concentration.

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

Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multi-scale nature of the interactions between aerosols, clouds and dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we use a multi-scale aerosol-climate model that treats aerosols and clouds across multiple scales to study aerosol indirect effects. This multi-scale aerosol-climate model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each vertical column of a GCM grid. The extension allows a more physically-based treatment of aerosol-cloud interactions in both stratiform and convective clouds on the global scale in a computationally feasible way. Simulated model fields, including liquid water path (LWP), ice water path, cloud fraction, shortwave and longwave cloud forcing, precipitation, water vapor, and cloud droplet number concentration are in reasonable agreement with observations. The new model performs quantitatively similar to the previous version of the MMF model in terms of simulated cloud fraction and precipitation. The simulated change in shortwave cloud forcing from anthropogenic aerosols is −0.77 W m−2, which is less than half of that (−1.79 W m−2) calculated by the host GCM (NCAR CAM5) with traditional cloud parameterizations and is also at the low end of the estimates of other conventional global aerosol-climate models. The smaller forcing in the MMF model is attributed to a smaller (3.9 %) increase in LWP from preindustrial conditions (PI) to present day (PD) compared with 15.6 % increase in LWP in stratiform clouds in CAM5. The difference is caused by a much smaller response in LWP to a given perturbation in cloud condensation nuclei (CCN) concentrations from PI to PD in the MMF (about one-third of that in CAM5), and, to a lesser extent, by a smaller relative increase in CCN concentrations from PI to PD in the MMF (about 26 % smaller than that in CAM5). The smaller relative increase in CCN concentrations in the MMF is caused in part by a smaller increase in aerosol lifetime from PI to PD in the MMF, a positive feedback in aerosol indirect effects induced by cloud lifetime effects from aerosols. The smaller response in LWP to anthropogenic aerosols in the MMF model is consistent with observations and with high resolution model studies, which may indicate that aerosol indirect effects simulated in conventional global climate models are overestimated and point to the need to use global high resolution models, such as MMF models or global CRMs, to study aerosol indirect effects. The simulated total anthropogenic aerosol effect in the MMF is −1.05 W m−2, which is close to the Murphy et al. (2009) inverse estimate of −1.1±0.4 W m−2 (1σ) based on the examination of the Earth's energy balance. Further improvements in the representation of ice nucleation and low clouds in MMF are needed to refine the aerosol indirect effect estimate.

Anthropogenic aerosol effects on climate produce one of the largest uncertainties in estimates of radiative forcing of past and future climate change. Much of this uncertainty arises from the multi-scale nature of the interactions between aerosols, clouds and large-scale dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we develop a multi-scale aerosol-climate model that treats aerosols and clouds across different scales, and evaluate the model performance, with a focus on aerosol treatment. This new model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each grid column of a GCM. In this extension, the effects of clouds on aerosols are treated by using an explicit-cloud parameterized-pollutant (ECPP) approach that links aerosol and chemical processes on the large-scale grid with statistics of cloud properties and processes resolved by the CRM. A two-moment cloud microphysics scheme replaces the simple bulk microphysics scheme in the CRM, and a modal aerosol treatment is included in the GCM. With these extensions, this multi-scale aerosol-climate model allows the explicit simulation of aerosol and chemical processes in both stratiform and convective clouds on a global scale. Simulated aerosol budgets in this new model are in the ranges of other model studies. Simulated gas and aerosol concentrations are in reasonable agreement with observations (within a factor of 2 in most cases), although the model underestimates black carbon concentrations at the surface by a factor of 2–4. Simulated aerosol size distributions are in reasonable agreement with observations in the marine boundary layer and in the free troposphere, while the model underestimates the accumulation mode number concentrations near the surface, and overestimates the accumulation mode number concentrations in the middle and upper free troposphere by a factor of about 2. The overestimation of accumulation model number concentrations in the middle and upper free troposphere is consistent with large aerosol mass fraction above 5 km in the MMF model compared with other models. Simulated cloud condensation nuclei (CCN) concentrations are within the observational variations. Simulated aerosol optical depths (AOD) are in reasonable agreement with observations (within a factor of 2), and the spatial distribution of AOD is consistent with observations, while the model underestimates AOD over regions with strong fossil fuel and biomass burning emissions. Overall, this multi-scale aerosol-climate model simulates aerosol fields as well as conventional aerosol models.

Aerosol particles in the lower atmosphere exert a substantial influence on climate and climate change through a variety of complex mechanisms. Consequently, there is a need to represent these influences in global climate models, and models have begun to include representations of these influences. However, the present treatment of aerosols in global climate models is highly simplified, omitting many processes and feedbacks that are thought to be climatically important. Thus, there is need for substantial improvement. Here we describe the strategy of the U.S. Department of Energy for improving representation of the properties, processes, and effects of tropospheric aerosols in global climate models. The strategy begins with a foundation of field and laboratory measurements that provide the basis for modules describing specific aerosol properties and processes. These modules are then integrated into regional aerosol models, which are evaluated by comparison with field measurements. Issues of scale are then addressed so that the modules can be applied to global aerosol models, which are evaluated by comparison with satellite retrievals and other observations. Finally, the validated set of modules is applied in global climate models for multicentury simulations. This strategy is expected to be applied to successive generations of global climate models.

© 2015. American Geophysical Union. All Rights Reserved. This study examines multiyear climate variability associated with sea salt aerosols and their contribution to the variability of shortwave cloud forcing (SWCF) using a 150 year simulation for preindustrial conditions of the Community Earth System Model version 1.0. The results suggest that changes in sea salt and related cloud and radiative properties on interannual timescales are dominated by the El Niño-Southern Oscillation cycle. Sea salt variability on longer (interdecadal) timescales is associated with low-frequency variability in the Pacific Ocean similar to the Interdecadal Pacific Oscillation but does not show a statistically significant spectral peak. A multivariate regression suggests that sea salt aerosol variability may contribute to SWCF variability in the tropical Pacific, explaining up to 20-30% of the variance in that region. Elsewhere, there is only a small sea salt aerosol influence on SWCF through modifying cloud droplet number and liquid water path that contributes to the change of cloud effective radius and cloud optical depth (and hence cloud albedo), producing a multiyear aerosol-cloud-wind interaction.

A global atmosphere–land model with an embedded subgrid orography scheme is used to simulate the period 1977–2100 using ocean surface conditions and radiative constituent concentrations for a climate change scenario. Climate variables simulated for multiple elevation classes are mapped according to a high-resolution elevation dataset in 10 regions with complex terrain. Analysis of changes in the simulated climate leads to the following conclusions. Changes in surface air temperature and precipitation differ from region to region in a manner similar to simulations without the subgrid scheme. Subgrid elevation contributes little to spatial variability of the change in temperature and the relative change in precipitation. In some regions somewhat greater warming occurs at higher elevations because of the same tendency in the free troposphere, but in others greater warming occurs near the melting level where snow albedo feedback amplifies the warming. Changes in snow water are highly dependent on altitude because of its nonlinear dependence on changes in the melting level. Absolute changes usually increase with altitude because more snow is currently available for depletion, but for extremely cold conditions the simulated warming is insufficient to increase melting. Relative changes in snow water always decrease with altitude as the likelihood that a warming will enhance melting or change the phase of precipitation decreases with decreasing temperature at higher altitudes. In places where snow accumulates, an artificial upper bound on snow water (which is required in any climate model that does not treat lateral snow transport) limits the sensitivity of snow water to climate change considerably. The simulated impact of climate change on regional mean snow water varies widely, with little impact in regions in which the upper bound on snow water is the dominant snow-water sink, moderate impact in regions with a mixture of seasonal and pemanent snow, and profound relative impacts on regions with little permanent snow.

The climate simulated by a global atmosphere–land model with a physically based subgrid orography scheme is evaluated in 10 selected regions. Climate variables simulated for each of multiple elevation classes within each grid cell are mapped according to a high-resolution distribution of surface elevation in each region. Comparison of the simulated annual mean climate with gridded observations leads to the following conclusions. At low to moderate elevations the downscaling scheme correctly simulates increasing precipitation, decreasing temperature, and increasing snow with increasing elevation across distances smaller than 100 km. At high elevations the downscaling scheme correctly simulates decreasing precipitation with increasing elevation. The rain shadow of many mountain ranges is poorly resolved, with too little precipitation simulated on the windward side of mountain ranges and too much on the lee side. The simulated sensitivity of surface air temperature to surface elevation is too strong, particularly in valleys influenced by drainage circulations. Observations show little evidence of a “snow shadow,” so the neglect of the subgrid rain shadow does not produce an unrealistic simulation of the snow distribution. Summertime snow area, which is a proxy for land ice, is much larger than observed, mostly because of excessive snowfall but in some places because of a cold bias. Summertime snow water equivalent is far less than the observed thickness of glaciers because a 1-m upper bound on snow water is applied to the simulations and because snow transport by slides is neglected. The 1-m upper bound on snow water equivalent also causes an underestimate of seasonal snow water during late winter, compared with gridded station measurements. Potential solutions to these problems are discussed.

A global atmosphere/land model with an embedded subgrid orography scheme is used to simulate the period 1977-2100 using ocean surface conditions and radiative constituent concentrations for a climate change scenario. Climate variables simulated for multiple elevation classes are mapping according to a high-resolution elevation dataset in ten regions with complex terrain. Analysis of changes in the simulated climate leads to the following conclusions. Changes in precipitation vary widely, with precipitation increasing more with increasing altitude in some region, decreasing more with altitude in others, and changing little in still others. In some regions the sign of the precipitation change depends on surface elevation. Changes in surface air temperature are rather uniform, with at most a two-fold difference between the largest and smallest changes within a region; in most cases the warming increases with altitude. Changes in snow water are highly dependent on altitude. Absolute changes usually increase with altitude, while relative changes decrease. In places where snow accumulates, an artificial upper bound on snow water limits the sensitivity of snow water to climate change considerably. The simulated impact of climate change on regional mean snow water varies widely, with little impact in regions in which the upper bound on snow water is the dominant snow water sink, moderate impact in regions with a mixture of seasonal and permanent snow, and profound impacts on regions with little permanent snow.

We present regional simulations of aerosol properties, direct radiative forcing and aerosol climatic effects over China, and compare the simulations with observed aerosol characteristics and climatic data over the region. The climate simulations are performed with a regional climate model, which is shown to capture the spatial distribution and seasonal pattern of temperature and precipitation. Aerosol concentrations are obtained from a global tracer-transport model and are provided to the regional model for the calculation of radiative forcing. Different aerosols are included: sulfate, organic carbon, black carbon, mineral dust, and sea salt and MSA particles. Generally, the aerosol optical depth is well simulated in both magnitude and spatial distribution. The direct radiative forcing of the aerosol is in the range –1 to –14 W m −2 in autumn and summer and −1 to –9 W m −2 in spring and winter, with substantial spatial variability at the regional scale. A strong maximum in aerosol optical depth and negative radiative forcing is found over the Sichuan Basin. The negative radiative forcing of aerosol induces a surface cooling in the range –0.6 to –1.2 °C in autumn and winter, –0.3 to –0.6 °C in spring and 0.0 to –0.9 °C in summer throughout East China. The aerosol-induced cooling is mainly due to a decrease in daytime maximum temperature. The cooling is maximum and is statistically significant over the Sichuan Basin. The effect of aerosol on precipitation is not evident in our simulations. The temporal and spatial patterns of the temperature trends observed in the second half of the twentieth century, including different trends for daily maximum and minimum temperature, are at least qualitatively consistent with the simulated aerosol-induced cooling over the Sichuan Basin and East China. This result supports the hypothesis that the observed temperature trends during the latter decades of the twentieth century, especially the cooling trends over the Sichuan Basin and some parts of East China, are at least partly related to the cooling induced by increasing atmospheric aerosol loadings over the region. DOI: 10.1046/j.1435-6935.2003.00070.x

Assessments of the impacts of climate change typically require information at scales of 10 km or less. Such a resolution in global climate simulations is unlikely for at least two decades. We have developed an alternative to explicit resolution that provides a framework for meeting the needs of climate change impact assessment much sooner. We have applied to a global climate model a physically based subgrid-scale treatment of the influence of orography on temperature, clouds, precipitation, and land surface hydrology. The treatment represents subgrid variations in surface elevation in terms of fractional area distributions of discrete elevation classes. For each class it calculates the height rise/descent of air parcels traveling through the grid cell, and applies the influence of the rise/descent to the temperature and humidity profiles of the elevation class. Cloud, radiative, and surface processes are calculated separately for each elevation class using the same physical parametrizations used by the model without the subgrid orography parametrization. The simulated climate fields for each elevation class can then be distributed in post-processing according to the spatial distribution of surface elevation within each grid cell. Parallel 10-year simulations with and without the subgrid treatment have been performed. The simulated temperature, precipitation and snow water are mapped to 2.5-minute (∼5 km) resolution and compared with gridded analyses of station measurements. The simulation with the subgrid scheme produces a much more realistic distribution of snow water and significantly more realistic distributions of temperature and precipitation than the simulation without the subgrid scheme. Moreover, the 250-km grid cell means of most other fields are virtually unchanged by the subgrid scheme. This suggests that the tuning of the climate model without the subgrid scheme is also applicable to the model with the scheme.

This study reports the Single-Column Model (SCM) part of the Atmospheric Radiation Measurement (ARM)/the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) joint SCM and Cloud-Resolving Model (CRM) Case 3 intercomparison study, with a focus on evaluation of cumulus parametrizations used in SCMs. Fifteen SCMs are evaluated under summertime midlatitude continental conditions using data collected at the ARM Southern Great Plains site during the summer 1997 Intensive Observing Period. Results from ten CRMs are also used to diagnose problems in the SCMs. It is shown that most SCMs can generally capture well the convective events that were well-developed within the SCM domain, while most of them have difficulties in simulating the occurrence of those convective events that only occurred within a small part of the domain. All models significantly underestimate the surface stratiform precipitation. A third of them produce large errors in surface precipitation and thermodynamic structures. Deficiencies in convective triggering mechanisms are thought to be one of the major reasons. Using a triggering mechanism that is based on the vertical integral of parcel buoyant energy without additional appropriate constraints results in overactive convection, which in turn leads to large systematic warm/dry biases in the troposphere. It is also shown that a non-penetrative convection scheme can underestimate the depth of instability for midlatitude convection, which leads to large systematic cold/moist biases in the troposphere. SCMs agree well quantitatively with CRMs in the updraught mass fluxes, while most models significantly underestimate the downdraught mass fluxes. Neglect of mesoscale updraught and downdraught mass fluxes in the SCMs contributes considerably to the discrepancies between the SCMs and the CRMs. In addition, uncertainties in the diagnosed mass fluxes in the CRMs and deficiencies with cumulus parametrizations are not negligible. Similar results are obtained in the sensitivity tests when different forcing approaches are used. Finally, sensitivity tests from an SCM indicate that its simulations can be greatly improved when its triggering mechanism and closure assumption are improved. © Royal Meteorological Society, 2002. J. C. Petch's contribution is Crown copyright.

Crop growth models, used in climate change impact assessments to project production on a local scale, can obtain the daily weather information to drive them from models of the Earth's climate. General Circulation Models (GCMs), often used for this purpose, provide weather information for the entire globe but often cannot depict details of regional climates especially where complex topography plays an important role in weather patterns. The U.S. Pacific Northwest is an important wheat growing region where climate patterns are difficult to resolve with a coarse scale GCM. Here, we use the PNNL Regional Climate Model (RCM) which uses a sub-grid parameterization to resolve the complex topography and simulate meteorology to drive the Erosion Productivity Impact Calculator (EPIC) crop model. The climate scenarios were extracted from the PNNL-RCM baseline and 2 × CO2 simulationsfor each of sixteen 90 km2 grid cells of the RCM, with differentiation byelevation and without correction for climate biases. The dominant agricultural soil type and farm management practices were established for each grid cell. Using these climate and management data in EPIC, we simulated winter wheat production in eastern Washington for current climate conditions (baseline) and a 2 × CO2 `greenhouse' scenario of climate change.Dryland wheat yields for the baseline climate averaged 4.52 Mg ha−1 across the study region. Yields were zero at high elevations where temperatures were too low to allow the crops to mature. The highest yields (7.32 Mgha−1) occurred at intermediate elevations with sufficientprecipitation and mild temperatures. Mean yield of dryland winter wheat increased to 5.45 Mg ha−1 for the 2 × CO2 climate, which wasmarkedly warmer and wetter. Simulated yields of irrigated wheat were generally higher than dryland yields and followed the same pattern but were, of course, less sensitive to increases in precipitation. Increases in dryland and irrigated wheat yields were due, principally, to decreases in the frequency of temperature and water stress. This study shows that the elevation of a farm is a more important determinant of yield than farm location in eastern Washington and that climate changes would affect wheat yields at all farms in the study.

We introduce an explicit emission tagging technique in the Community Atmosphere Model to quantify source-region-resolved characteristics of black carbon (BC), focusing on the Arctic. Explicit tagging of BC source regions without perturbing the emissions makes it straightforward to establish source-receptor relationships and transport pathways, providing a physically consistent and computationally efficient approach to produce a detailed characterization of the destiny of regional BC emissions and the potential for mitigation actions. Our analysis shows that the contributions of major source regions to the global BC burden are not proportional to the respective emissions due to strong region-dependent removal rates and lifetimes, while the contributions to BC direct radiative forcing show a near-linear dependence on their respective contributions to the burden. Distant sources contribute to BC in remote regions mostly in the mid- and upper troposphere, having much less impact on lower-level concentrations (and deposition) than on burden. Arctic BC concentrations, deposition and source contributions all have strong seasonal variations. Eastern Asia contributes the most to the wintertime Arctic burden. Northern Europe emissions are more important to both surface concentration and deposition in winter than in summer. The largest contribution to Arctic BC in the summer is from Northern Asia. Although local more » emissions contribute less than 10% to the annual mean BC burden and deposition within the Arctic, the per-emission efficiency is much higher than for major non-Arctic sources. The interannual variability (1996-2005) due to meteorology is small in annual mean BC burden and radiative forcing but is significant in yearly seasonal means over the Arctic. When a slow aging treatment of BC is introduced, the increase of BC lifetime and burden is source-dependent. Global BC forcing-per-burden efficiency also increases primarily due to changes in BC vertical distributions. The relative contribution from major non-Arctic sources to the Arctic BC burden increases only slightly, although the contribution of Arctic local sources is reduced by a factor of 2 due to the slow aging treatment. « less

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by -2.5 and +1.3 W m(-2), respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors' knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.

Atmospheric black carbon (BC) absorbs solar radiation, and exacerbates global warming through exerting positive radiative forcing (RF). However, the contribution of BC to ongoing changes in global climate is under debate. Anthropogenic BC emissions, and the resulting distribution of BC concentration, are highly uncertain. In particular, long range transport and processes affecting BC atmospheric lifetime are poorly understood. Here we discuss whether recent assessments may have overestimated present day BC radiative forcing in remote regions. We compare vertical profiles of BC concentration from four recent aircraft measurement campaigns to simulations by 13 aerosol models participating in the AeroCom Phase II intercomparision. An atmospheric lifetime of BC of less than 5 days is shown to be essential for reproducing observations in remote ocean regions, in line with other recent studies. Adjusting model results to measurements in remote regions, and at high altitudes, leads to a 25% reduction in AeroCom Phase II median direct BC forcing, from fossil fuel and biofuel burning, over the industrial era. The sensitivity of modeled forcing to BC vertical profile and lifetime highlights an urgent need for further flight campaigns, close to sources and in remote regions, to provide improved quantification of BC effects for use in climate policy.

Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol–climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate.

Eleven different single-column models (SCMs) and one cloud ensemble model (CEM) are driven by boundary conditions observed at the Atmospheric Radiation Measurement (ARM) program southern Great Plains site for a 17 day period during the summer of 1995. Comparison of the model simulations reveals common signatures identifiable as products of errors in the boundary conditions. Intermodel differences in the simulated temperature, humidity, cloud, precipitation, and radiative fluxes reflect differences in model resolution or physical parameterizations, although sensitive dependence on initial conditions can also contribute to intermodel differences. All models perform well at times but poorly at others. Although none of the SCM simulations stands out as superior to the others, the simulation by the CEM is in several respects in better agreement with the observations than the simulations by the SCMs. Nudging of the simulated temperature and humidity toward observations generally improves the simulated cloud and radiation fields as well as the simulated temperature and humidity but degrades the precipitation simulation for models with large temperature and humidity biases without nudging. Although some of the intermodel differences have not been explained, others have been identified as model problems that can be or have been corrected as a result of the comparison.

Parallel simulations of clouds and radiation fields by a single-column model (SCM), a regional circulation model, and a global circulation model (GCM), each using the same treatment of all physical processes and approximately the same spatial resolution, are compared with observations at the Atmopheric Radiation Measurement Clouds and Radiation Testbed in the southern Great Plains. Significant differences between model simulations are evident for individual cloud systems, but these differences are not systematic, varying from cloud system to cloud system. Several systematic differences between model simulations and observations are identified. These biases are about the same for each model and are much larger than differences between model simulations, suggesting that for some purposes one model can serve as a testbed for parameterizations developed for another. The role of nudging in the simulations is explored by driving the SCM with large-scale forcing from a GCM simulation. The authors find t...

Global climate change due to increasing concentrations of greenhouse gases has stimulated numerous studies and discussions about its possible impacts on water resources. Climate scenarios generated by climate models at spatial resolutions ranging from about 50 km to 400 km may not provide enough spatial specificity for use in impact assessment. In Parts I and II of this paper, the spatial specificity issue is addressed by examining what information on mesoscale and small-scale spatial features can be gained by using a regional climate model with a subgrid parameterization of orographic precipitation and land surface cover, driven by a general circulation model. Numerical experiments have been performed to simulate the present-day climatology and the climate conditions corresponding to a doubling of atmospheric CO 2 concentration. This paper describes and contrasts the large-scale and mesoscale features of the greenhouse warming climate signals simulated by the general circulation model and regional climate model over the Pacific Northwest. Results indicate that changes in the large-scale circulation exhibit strong seasonal variability. There is an average warming of about 28C, and precipitation generally increases over the Pacific Northwest and decreases over California. The precipitation signal over the Pacific Northwest is only statistically significant during spring, when both the change in the large-scale circulation and increase in water vapor enhance the moisture convergence toward the north Pacific coast. The combined effects of surface temperature and precipitation changes are such that snow cover is reduced by up to 50% on average, causing large changes in the seasonal runoff. This paper also describes the high spatial resolution (1.5 km) climate signals simulated by the regional climate model. Reductions in snow cover of 50%‐90% are found in areas near the snow line of the control simulation. Analyses of the variations of the climate signals with surface elevation ranging from sea level to 4000 m over two mountain ranges in the Pacific Northwest show that because of changes in the alitude of the freezing level, strong elevation dependency is found in the surface temperature, rainfall, snowfall, snow cover, and runoff signals.

Regional climate models have become a common research tool for downscaling global climate simulations. To further examine their usefulness for climate studies and the impacts that different physical parameterizations have on the simulations, an intercomparison experiment has been performed where three regional climate models are used to simulate an extreme flood event. Although the dynamical components of the models are almost identical, the physical parameterizations used to represent clouds, radiative transfer, turbulence transport, and surface processes are very different. The models were used to simulate the heavy precipitation during the 1991 summer which caused severe flooding over the Yangtze River in China. This extreme event is selected to highlight the differences among regional climate models. Results from the intercomparison show that all models simulated the gross flood conditions reasonably well, although each model reproduced the observed rainband to varying degrees, and significant differences are found in the simulated energy and hydrological cycles, especially over cloudy areas. Through detailed analyses of model simulations at different spatial and temporal scales, several reasons are found to cause the departure of model simulations from each other. These include the simulation of the amount and vertical distribution of clouds, the treatment of cloud-radiative feedbacks, and the representation of land surface processes. This study suggests that aspects other than surface temperature and precipitation of the regional climate simulations need to be more carefully evaluated. One specially important evaluation criterion is the radiation balance which has serious implications for long-term climate simulations.

Previous development of the Pacific Northwest National Laboratory’s regional climate model has focused on representing orographic precipitation using a subgrid parameterization where subgrid variations of surface elevation are aggregated to a limited number of elevation classes. An airflow model and a thermodynamic model are used to parameterize the orographic uplift/descent as air parcels cross over mountain barriers or valleys. This paper describes further testing and evaluation of this subgrid parameterization. Building upon this modeling framework, a subgrid vegetation scheme has been developed based on statistical relationships between surface elevation and vegetation. By analyzing high-resolution elevation and vegetation data, a dominant land cover is defined for each elevation band of each model grid cell to account for the subgrid heterogeneity in vegetation. When larger lakes are present, they are distinguished from land within elevation bands and a lake model is used to simulate the the...

A 6.25-km resolution dataset of meteorology, vegetation type, and soil type for a domain covering a typical global climate model grid cell is used to drive a land surface physics model for a period of 6 months. Additional simulations are performed driving the land surface physics model by spatially averaged meteorology, spatially averaged vegetation characteristics, spatially averaged soil properties, and spatially averaged meteorology, vegetation characteristics, and soil properties. By comparing the simulated water balance for the whole domain for each simulation, the relative influence of subgrid variability in meteorology, vegetation, and soil are assessed. Subgrid variability in summertime precipitation is found to have the largest effect on the surface hydrology, with a nearly twofold increase on surface runoff and a 15% increase in evapotranspiration. Subgrid variations in vegetation and soil properties also increase surface runoff and reduce evapotranspiration, so that surface runoff is 2.75 times as great with subgrid variability than without and evapotranspiration is 19% higher with subgrid variability than without.

Simulated multi-model "diversity" in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated "host-model uncertainties" are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is −4.47 Wm−2 and the inter-model standard deviation is 0.55 Wm−2, corresponding to a relative standard deviation of 12%. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04 Wm−2, and the standard deviation increases to 1.01 W−2, corresponding to a significant relative standard deviation of 97%. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45 Wm−2 (8%) clear-sky and 0.62 Wm−2 (11%) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the AeroCom Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11 Wm−2 in the AeroCom Direct Radiative Effect experiment. Host model errors in aerosol radiative forcing are largest in regions of uncertain host model components, such as stratocumulus cloud decks or areas with poorly constrained surface albedos, such as sea ice. Our results demonstrate that host model uncertainties are an important component of aerosol forcing uncertainty that require further attention.

We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02 Wm−2, with a mean of −0.27 Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35 Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study. We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results.

Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multi-year database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, sea-salt, sulfate, black and organic carbon). We use 9 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS (2 products), TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDER and MSG/SEVIRI, as well as 3 more historical datasets: NIMBUS7/CZCS, TOMS (onboard NIMBUS7 and Earth-Probe) and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, the multi-model mean coming from the ACCMIP exercise, and the reanalyses GEMS and MACC. Ground-based Level-2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatio-temporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain datasets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data, but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences of vertical distribution between dust aerosols showing a large vertical spread, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003–2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology. We extend the 2003–2009 reconstruction to the past up to 1979 using the 2003–2009 average and applying the decreasing trend in sulfate aerosols from LMDz-OR-INCA, whose AOD trends over Europe and the Mediterranean are median among the ACCMIP models. Finally optical properties of the different aerosol types in this region are proposed from Mie calculations so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosol-climate studies.