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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.

One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the sub-grid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol sub-grid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry (WRF-Chem). We find that within a typical GCM grid, the aerosol mass sub-grid standard deviation is 15% of the grid-box mean mass near the surface on a 1-month mean basis. The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol sub-grid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km to 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between the sub-grid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R>0.95. despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER(2.1)) is significantly smaller than that based on the 3.7 µm band (CER(3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(3.7) and CER(2.1) retrievals have a lower correlation (R~0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

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.

Wet scavenging of aerosols by continental deep convective clouds is studied for a supercell storm complex observed over Oklahoma during the Deep Convective Clouds and Chemistry campaign. A new passive-tracer-based transport analysis framework is developed to characterize convective transport using vertical profiles of several passive trace gases. For this case, the analysis estimates that observed passive gas mixing ratios in the upper troposphere convective outflow consist of 47% low level (

Secondary organic aerosols (SOA) are large contributors to fine-particle loadings and radiative forcing but are often represented crudely in global models. We have implemented three new detailed SOA treatments within the Community Atmosphere Model version 5 (CAM5) that allow us to compare the semivolatile versus nonvolatile SOA treatments (based on some of the latest experimental findings) and to investigate the effects of gas-phase fragmentation reactions. The new treatments also track SOA from biomass burning and biofuel, fossil fuel, and biogenic sources. For semivolatile SOA treatments, fragmentation reactions decrease the simulated annual global SOA burden from 7.5 Tg to 1.8 Tg. For the nonvolatile SOA treatment with fragmentation, the burden is 3.1 Tg. Larger differences between nonvolatile and semivolatile SOA (up to a factor of 5) exist in areas of continental outflow over the oceans. According to comparisons with observations from global surface Aerosol Mass Spectrometer measurements and the U.S. Interagency Monitoring of Protected Visual Environments (IMPROVE) network measurements, the FragNVSOA treatment, which treats SOA as nonvolatile and includes gas-phase fragmentation reactions, agrees best at rural locations. Urban SOA is underpredicted, but this may be due to the coarse model resolution. All three revised treatments show much better agreement with aircraft measurements of organic aerosols (OA) over the North American Arctic and sub-Arctic in spring and summer, compared to the standard CAM5 formulation. This is mainly due to the oxidation of SOA precursor gases from biomass burning, not included in standard CAM5, and long-range transport of biomass burning OA at high altitudes. The revised model configurations that include fragmentation (both semivolatile and nonvolatile SOA) show much better agreement with MODerate resolution Imaging Spectrometers (MODIS) aerosol optical depth data over regions dominated by biomass burning during the summer compared to standard CAM5, and predict biomass burning and biofuel as the largest global source of OA, followed by biogenic and fossil fuel sources. The large contribution of biomass burning OA in the revised treatments is supported by these measurements, but the emissions and aging of SOA precursors and POA are uncertain, and need further investigation. The nonvolatile and semivolatile configurations with fragmentation predict the direct radiative forcing of SOA as −0.5 W m−2 and −0.26 W m−2 respectively, at top of the atmosphere, which are higher than previously estimated by most models, but in reasonable agreement with a recent constrained modeling study. This study highlights the importance of improving process-level representation of SOA in global models.

Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the mid-latitude continental and the tropical regions are conducted and evaluated, we examine the scale-dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraft eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of 38 mid-latitude continental convection. We show that the single updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as 3 updrafts can account for the internal variability of updrafts well.more » Based on evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.« less

The ultimate goal of this study is to improve the representation of convective transport by cumulus parameterization for mesoscale and climate models. As Part 1 of the study, we perform extensive evaluations of cloud-resolving simulations of a squall line and mesoscale convective complexes in midlatitude continent and tropical regions using the Weather Research and Forecasting model with spectral bin microphysics (SBM) and with two double-moment bulk microphysics schemes: a modified Morrison (MOR) and Milbrandt and Yau (MY2). Compared to observations, in general, SBM gives better simulations of precipitation and vertical velocity of convective cores than MOR and MY2 and therefore will be used for analysis of scale dependence of eddy transport in Part 2. The common features of the simulations for all convective systems are (1) the model tends to overestimate convection intensity in the middle and upper troposphere, but SBM can alleviate much of the overestimation and reproduce the observed convection intensity well; (2) the model greatly overestimates Ze in convective cores, especially for the weak updraft velocity; and (3) the model performs better for midlatitude convective systems than the tropical system. The modeled mass fluxes of the midlatitude systems are not sensitive to microphysics schemes but are very sensitive for the tropical case indicating strong microphysics modification to convection. Cloud microphysical measurements of rain, snow, and graupel in convective cores will be critically important to further elucidate issues within cloud microphysics schemes.

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.

Most estimates of the global mean indirect effect of anthropogenic aerosol on the Earth's energy balance are from simulations by global models of the aerosol lifecycle coupled with global models of clouds and the hydrologic cycle. Extremely simple models have been developed for integrated assessment models, but lack the flexibility to distinguish between primary and secondary sources of aerosol. Here a simple but more physically based model expresses the aerosol indirect effect (AIE) using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of AIEs that are comparable to those from some global aerosol models using the same global mean aerosol properties, the estimates by the simple model are sensitive to preindustrial cloud condensation nuclei concentration, preindustrial accumulation mode radius, width of the accumulation mode, size of primary particles, cloud thickness, primary and secondary anthropogenic emissions, the fraction of the secondary anthropogenic emissions that accumulates on the coarse mode, the fraction of the secondary mass that forms new particles, and the sensitivity of liquid water path to droplet number concentration. Estimates of present-day AIEs as low as 5 W/sq m and as high as 0.3 W/sq m are obtained for plausible sets of parameter values. Estimates are surprisingly linear in emissions. The estimates depend on parameter values in ways that are consistent with results from detailed global aerosol-climate simulation models, which adds to understanding of the dependence on AIE uncertainty on uncertainty in parameter values.

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.

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.

Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When sub-columns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified By Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continental and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species, - a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the sub-column generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.

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

Estimates of direct and indirect radiative forcing by anthropogenic sulfate aerosols from an integrated global aerosol and climate modeling system are presented. A detailed global tropospheric chemistry and aerosol model that predicts concentrations of oxidants as well as aerosols and aerosol precursors, is coupled to a general circulation model that predicts both cloud water mass and cloud droplet number. Both number and mass of several externally-mixed aerosol size modes are predicted, with internal mixing assumed for the different aerosol components within each mode. Predicted aerosol species include sulfate, organic and black carbon, soil dust, and sea salt. The models use physically-based treatments of aerosol radiative properties (including dependence on relative humidity) and aerosol activation as cloud condensation nuclei. Parallel simulations with and without anthropogenic sulfate aerosol are performed for a global domain. The global and annual mean direct and indirect radiative forcing due to anthropogenic sulfate are estimated to be -0.3 to -0.5 and -1.5 to -3.0 W m-2, respectively. The radiative forcing is sensitive to the model's horizontal resolution, the use of predicted vs. analyzed relative humidity, the prediction vs. diagnosis of aerosol number and droplet number, and the parameterization of droplet collision/coalescence. About half of the indirect radiativemore » forcing is due to changes in droplet radius and half to increased cloud liquid water.« less

A parameterization of the activation of a lognormal size distribution of aerosols to form cloud droplets is extended to the case of multiple externally mixed lognormal modes, each composed of a uniform internal mixture of soluble and insoluble material. The Kohler theory is used to relate the aerosol size distribution and composition to the number activated as a function of maximum supersaturation. The supersaturation balance is used to determine the maximum supersaturation, accounting for particle growth both before and after the particles are activated. Comparison of the parameterized activation of two competing aerosol modes with detailed numerical simulations of the activation process yields agreement to within 10% under a wide variety of conditions, including diverse size distributions, number concentrations, compositions, and updraft velocities. The parametization error exceeds 10% only when the mode radius of the two size distributions differs by an order of magnitude. Errors for the mass fraction activated are always much less than errors for the number fraction activated.

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.

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.

This paper presents a parameterization of the fraction of aerosol particles activated to form cloud droplets in a parcel of air rising adiabatically. The study applies to aerosols of a single lognormal size distribution with uniform chemical composition and capable of serving as cloud condensation nuclei. The parameterization is based on analysis of the rate equations for the parcel supersaturation and aerosol activation process. The analysis leads to the identification of only four dimensionless parameters on which the fraction of activation strongly depends. Using results of detailed numerical simulations by a size-resolving Lagrangian parcel model, errors due to simplifying assumptions used in the analysis were largely eliminated by employing adjustment coefficients. For a wide range of governing parameters (e.g., particle radius, standard deviation, updraft velocity, etc.), differences between the parametric equations and the numerical model results are less than 10% for most conditions and less than 25% for some extreme but realistic conditions. This new parameterization is significantly more accurate and successful in representing the fraction of activation in terms of governing parameters than any known parameterization.

A predictive treatment of droplet number is applied to both a single-column cloud model and a global circulation model. Droplet number is predicted from the droplet number balance, which accounts for droplet nucleation, mixing, and droplet loss due to autoconversion of droplets to rain and collection by rain, ice, and snow. Droplet nucleation is parameterized in terms of the parameters of a lognormal aerosol size distribution and in terms of a Gaussian probability distribution of vertical velocity within each grid cell. The predicted droplet number is found to be significantly less than observations unless vertical resolution provides at least 10 levels within the planetary boundary layer. When droplet number is simply diagnosed from the number nucleated, droplet concentrations are found to be consistently greater than with the predictive treatment. Predicted droplet number concentrations are found to be nonlinearly related to aerosol number concentration.

The Colorado State University Regional Atmospheric Modeling System bulk cloud microphysics parameterization has been applied to the treatment of stratiform clouds in the National Center for Atmospheric Research community climate model. Predicted cloud properties are mass concentrations of cloud water, cloud ice, rain, and snow and number concentration of ice. Microphysical processes treated include condensation of water vapor and evaporation of cloud water and rain, nucleation of ice crystals, vapor deposition and sublimation of cloud ice and snow, autoconversion and accretion of cloud water, aggregation and collection of cloud ice, melting of ice and snow, riming on ice and snow, and gravitational settling of ice, rain, and snow. Although the parameterization is more detailed and hence more computationally demanding than other cloud microphysics parameterizations in climate models, it treats the Bergeron-Findeisen process explicitly and hence does not require an ad hoc parameterization to distinguish liquid water and ice. A variety of simulations were performed, testing sensitivity to horizontal and vertical resolution, the treatment of ice number, droplet number, and parameterization of cumulus convection. The simulated planetary radiation balance is found to be particularly sensitive to the treatment of ice number and cumulus convection.

A regional climate model including a physically based parameterization of the subgrid effects of topography on clouds and precipitation is driven by observed meteorology on its lateral boundaries for a period of 12 months. The meteorology simulated by the model for each subgrid elevation class is distributed across a mountain watershed according to the surface elevation within the watershed. The simulated meteorology is used to drive a detailed model of hydrology-vegetation dynamics at the topographic scale described by digital elevation data, 180 m. The watershed model, which includes a two-layer canopy model for evapotranspiration, an energy-balance model for snow accumulation and melt, a two-layer rooting zone model, and a quasi-three-dimensional saturated subsurface flow model, is used to simulate the seasonal cycle of the accumulation and melt of snow and the accumulation and discharge of surface water within a mountain watershed in northwestern Montana. Comparisons between the simulated and the recorded snow cover and river discharge at the base of the watershed indicate comparable if not better agreement than between the recorded fields and those simulated by the watershed model driven by meteorology observed at two stations within the watershed. The agreement with the recorded discharge, precipitation, and snow water equivalent is also clearly superior to simulations driven by the regional climate model run without the subgrid parameterization but with one-third the grid size of the simulation with the subgrid parameterization.

Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state-of-the-art global climate models (GCM), especially those in which embedded cloud-resolving models replace conventional statistical parameterizations (i.e., multiscale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre-industrial and present-day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten-year GCM simulations with nudging provide a more stable estimate of the global-annual mean net aerosol indirect radiative forcing than do conventional free-running simulations. The estimates have mean values and 95% confidence intervals of −1.19 ± 0.02 W/m2 and −1.37 ± 0.13 W/m2for nudged and free-running simulations, respectively. Nudging also substantially increases the fraction of the world's area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earth's surface for nudged and free-running simulations, respectively). One-year MMF simulations with and without nudging provide global-annual mean net aerosol indirect radiative forcing estimates of −0.81 W/m2 and −0.82 W/m2, respectively. These results compare well with previous estimates from three-year free-running MMF simulations (−0.83 W/m2), which showed the aerosol-cloud relationship to be in better agreement with observations and high-resolution models than in the results obtained with conventional cloud parameterizations.

[1] Remote sensing observations of aerosol from surface and satellite instruments are extensively used for atmospheric and climate research. From passive sensors, the apparent cloud-free atmosphere in the vicinity of clouds often appears to be brighter than further away from the clouds, leading to an increase in the retrieved aerosol optical depth (τ). Mechanisms contributing to this enhancement or increase, including contamination by undetected clouds, hygroscopic growth of aerosol particles, and meteorological conditions, have been debated in recent literature, but the extent to which each of these factors influence the observed enhancement (Δτ) is poorly known. Here we used 11 years of daily global observations at 10 × 10 km2 resolution from the MODIS on the NASA Terra satellite to quantify τ as a function of cloud fraction (CF). Our analysis reveals that, averaged over the globe, the clear sky τ is enhanced by Δτ = 0.05 in cloudy conditions (CF = 0.8–0.9). This enhancement in Δτ corresponds to relative enhancement of 25% in cloudy conditions (CF = 0.8–0.9) compared with relatively clear conditions (CF = 0.1–0.2). Unlike the absolute enhancement Δτ, the relative increase in τis rather consistent in all seasons and is 25–35% in the subtropics and 15–25% at mid and higher latitudes. Using a simple Gaussian probability density function model to connect cloud cover and the distribution of relative humidity, we argue that much of the enhancement is consistent with aerosol hygroscopic growth in the humid environment surrounding clouds. Consideration of these cloud-dependentτeffects will facilitate understanding aerosol-cloud interactions and reduce the uncertainty in estimates of aerosol radiative forcing by global climate models.

The CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) layer product is used for a multimodel evaluation of the vertical distribution of aerosols. Annual and seasonal aerosol extinction profiles are analyzed over 13 sub-continental regions representative of industrial, dust, and biomass burning pollution, from CALIOP 2007-2009 observations and from AeroCom (Aerosol Comparisons between Observations and Models) 2000 simulations. An extinction mean height diagnostic (Z-alpha) is defined to quantitatively assess the models' performance. It is calculated over the 0-6 km and 0-10 km altitude ranges by weighting the altitude of each 100 m altitude layer by its aerosol extinction coefficient. The mean extinction profiles derived from CALIOP layer products provide consistent regional and seasonal specificities and a low inter-annual variability. While the outputs from most models are significantly correlated with the observed Z-alpha climatologies, some do better than others, and 2 of the 12 models perform particularly well in all seasons. Over industrial and maritime regions, most models show higher Z-alpha than observed by CALIOP, whereas over the African and Chinese dust source regions, Z-alpha is underestimated during Northern Hemisphere Spring and Summer. The positive model bias in Z-alpha is mainly due to an overestimate of the extinction above 6 km. Potential CALIOP and model limitations, and methodological factors that might contribute to the differences are discussed.

[1] The optical properties of an internally mixed aerosol with a lognormal size distribution can be approximated in terms of analytic functions of the wet surface mode radius with coefficients that can be related to the wet refractive index. The wet radius is calculated from the dry radius and relative humidity using either the Kohler theory or the MOSAIC thermodynamic model. The hydration state of the aerosol in the hysteresis region between the crystallization and deliquescence relative humidities is diagnosed by comparing the aerosol water from the previous time step with the current water content of the hydrated aerosol. The wet refractive index is estimated from the volume fractions and refractive indices of all components of the aerosol, including water, using volume mixing for soluble components and an effective medium approximation for the insoluble components. The parameterization is evaluated by comparing with Mie solutions for ammonium sulfate, black carbon, and a 50:50 mixture for a wide range in size distributions and relative humidity. Errors are usually less than 20% and are less then 30% for all conditions except when absolute values are small. The parameterization is suitable for any aerosol model that uses lognormal size distributions composed of internal mixtures of multiple aerosol components.

[1] This paper examines the effects of slightly soluble organics on aerosol activation in a parcel of air rising adiabatically. Slightly soluble organics can affect aerosol activation by three mechanisms: lowering surface tension, altering the bulk hygroscopicity, and delaying the growth of particles because of their lower solubilities. The first and second mechanisms have already been addressed in a previous paper. Here we address the third mechanism by simulating the activation process of aerosol particles modeled using a single lognormal size distribution and consisting of an internal uniform chemical mixture of adipic acid (representing slightly soluble organics having extremely low solubility as a worst-case scenario) and ammonium sulfate. The simulations were carried out using measured solubility of adipic acid spanning a wide range of physical and dynamical parameters. The same conditions were resimulated but assuming fully soluble aerosols. Results of the simulations show that although the low solubility of the adipic acid alters Kohler curves and increases critical supersaturation of the smaller particles (Kohler curves of the larger particles are not affected because these particles are completely dissolved at the initial supersaturation of zero), low solubility has minimal to no effect on the parcel supersaturation except for particles consisting of more than 95% adipic acid. Furthermore, since aerosols in realistic atmospheric conditions do not contain more than 90% organics, we should be only interested in smaller concentrations (less than 90% by mass). Accordingly, we conclude that the slightly soluble organics can be assumed to be fully soluble for the purpose of predicting the fraction of activation and the maximum supersaturation with negligible error and it is not necessary to retune the previously developed parameterization of aerosol activation.

[1] A triple-moment sectional (TMS) aerosol dynamics model, Modal Bin Hybrid Model (MBHM), has been developed. In addition to number and mass (volume), surface area is predicted (and preserved), which is important for aerosol processes and properties such as gas-to-particle mass transfer, heterogeneous reaction, and light extinction cross section. The performance of MBHM was evaluated against double-moment sectional (DMS) models with coarse (BIN4) to very fine (BIN256) size resolutions for simulating evolution of particles under simultaneously occurring nucleation, condensation, and coagulation processes (BINx resolution uses x sections to cover the 1 nm to 1 µm size range). Because MBHM gives a physically consistent form of the intrasectional distributions, errors and biases of MBHM at BIN4-8 resolution were almost equivalent to those of DMS at BIN16–32 resolution for various important variables such as the moments Mk (k: 0, 2, 3), dMk/dt, and the number and volume of particles larger than a certain diameter. Another important feature of MBHM is that only a single bin is adequate to simulate full aerosol dynamics for particles whose size distribution can be approximated by a single lognormal mode. This flexibility is useful for process-oriented (multicategory and/or mixing state) modeling: Primary aerosols whose size parameters would not differ substantially in time and space can be expressed by a single or a small number of modes, whereas secondary aerosols whose size changes drastically from 1 to several hundred nanometers can be expressed by a number of modes. Added dimensions can be applied to MBHM to represent mixing state or photochemical age for aerosol mixing state studies.

[1] Surface-active organic compounds, or surfactants, can affect aerosol activation by two mechanisms: lowering surface tension and altering the bulk hygroscopicity of the particles. A numerical model has been developed to predict the activation of aerosol particles consisting of an internally uniform chemical mixture of organic surfactants and inorganic salts in a parcel of air rising adiabatically at constant speed. Equations reflecting water balance of the air parcel were used together with a modified form of Kohler theory to model droplet nucleation while considering surface effects. We also extend a parametric representation of aerosol activation to the case of a mixture of inorganic salts and organic surfactants by modifying the Raoult term in Kohler theory (assuming additive behavior) and using a simplified relationship between surface tension and surfactant molar concentration to account for surface effects at the critical radius for activation. The close agreement (to within 10% for most and 20% for almost all conditions) between numerical and parametric results validates our modifications. Moreover, the form of the relationship is identical to an empirical relationship between surface tension and organic carbon concentration. Thus the modified form of the parameterization provides a framework that can account for the influence of observed organics on the activation of other salts. The modified form of the parameterization is tested successfully with the Po Valley model both for single aerosol size distribution and three-mode size distributions for marine, rural, and urban aerosols. Further measurements are required to extend the parameterization to other organic surfactants.

[1] The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the parameterizations. Finally, SCMs are run for a 24–48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24–48 hr runs suggest that most models have problems in simulating boundary layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.

[1] The effect of various wind speed averaging periods on calculated dimethylsulfide (DMS) emission fluxes is quantitatively assessed. A global climate model and an emission flux module were run in stand-alone mode for a full year. Twenty-minute instantaneous surface wind speeds and related variables generated by the climate model were archived, and corresponding 1-hour, 6-hour, daily, and monthly averaged quantities were calculated. These various time-averaged, model-derived quantities were used as inputs in the emission flux module, and DMS emissions were calculated using two expressions for the mass transfer velocity commonly used in atmospheric models [Liss and Merlivat, 1986; Nightingale et al., 2000]. Results indicate that the time period selected for averaging wind speeds can affect the magnitude of calculated DMS emission fluxes. A number of individual marine cells within the global grid show DMS emissions fluxes that are 10–60% higher when emissions are calculated using 20-min instantaneous model time step winds rather than monthly averaged wind speeds, and at some locations the differences exceed 200%. Many of these cells are located in the Southern Hemisphere where anthropogenic sulfur emissions are low and changes in oceanic DMS emissions may significantly affect calculated aerosol concentrations and aerosol radiative forcing.

[1] We use a one-dimensional version of a climate-aerosol-chemistry model with both modal and sectional aerosol size representations to evaluate the impact of aerosol size representation on modeling aerosol-cloud interactions in shallow stratiform clouds observed during the second Aerosol Characterization Experiment. Both the modal (with prognostic aerosol number and mass or prognostic aerosol number, surface area and mass, referred to as the Modal-NM and Modal-NSM) and the sectional approaches (with 12 and 36 sections) predict total number and mass for interstitial and activated particles that are generally within several percent of references from a high-resolution 108-section approach. The modal approach with prognostic aerosol mass but diagnostic number (referred to as the Modal-M) cannot accurately predict the total particle number and surface areas, with deviations from the references ranging from 7 to 161%. The particle size distributions are sensitive to size representations, with normalized absolute differences of up to 12% and 37% for the 36- and 12-section approaches, and 30%, 39%, and 179% for the Modal-NSM, Modal-NM, and Modal-M, respectively. For the Modal-NSM and Modal-NM, differences from the references are primarily due to the inherent assumptions and limitations of the modal approach. In particular, they cannot resolve the abrupt size transition between the interstitial and activated aerosol fractions. For the 12- and 36-section approaches, differences are largely due to limitations of the parameterized activation for nonlognormal size distributions, plus the coarse resolution for the 12-section case. Differences are larger both with higher aerosol (i.e., less complete activation) and higher SO2 concentrations (i.e., greater modification of the initial aerosol distribution).