S. E. Bauer

Columbia University, New York, New York, United States

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Publications (72)289.19 Total impact

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    ABSTRACT: Atmospheric black carbon (BC) absorbs solar ra-diation, 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 life-time are poorly understood. Here we discuss whether recent assessments may have overestimated present-day BC radia-tive 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 intercomparison. 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 mea-surements in remote regions, and at high altitudes, leads to a 25 % reduction in AeroCom Phase II median direct BC forc-ing, from fossil fuel and biofuel burning, over the industrial era. The sensitivity of modelled forcing to BC vertical pro-file and lifetime highlights an urgent need for further flight campaigns, close to sources and in remote regions, to pro-vide improved quantification of BC effects for use in climate policy.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 11/2014; 142021(13):12465-12477. DOI:10.5194/acp-14-12465-2014 · 5.30 Impact Factor
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    ABSTRACT: Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this investigation we compare aerosols, clouds, and their interactions in three global climate models (GFDL-AM3, NCAR-CAM5, GISS-ModelE2) to MODIS satellite observations. Modeled cloud properties are diagnosed using a MODIS simulator. Cloud droplet number concentrations (N) are computed identically from satellite-simulated and MODIS-observed values of liquid cloud optical depth and droplet effective radius. We find that aerosol optical depth (τa) simulated by models is similar to observations in many regions around the globe. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in coastal marine stratocumulus versus remote ocean regions, though modeled values in general are higher than observed. Aerosol-cloud interactions were computed as the sensitivity of ln(N) to ln(τa) for coastal marine liquid clouds near South Africa (SAF) and Southeast Asia (SEA) where τa varies in time. AM3 and CAM5 are more sensitive than observations, while the sensitivity for ModelE2 is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the sensitivity of ln(N) to ln(τa) at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite-simulated versus standard model values of N from CAM5 are compared in SAF; standard model values are significantly lower with a bias of 83 cm−3.
    Journal of Geophysical Research Atmospheres 09/2014; DOI:10.1002/2014JD021722 · 3.44 Impact Factor
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    ABSTRACT: Observations of climate change during the CMIP5 extended historical period (1850-2012) are compared to trends simulated by six versions of the NASA Goddard Institute for Space Studies ModelE2 Earth System Model. The six models are constructed from three versions of the ModelE2 atmospheric general circulation model, distinguished by their treatment of atmospheric composition and the aerosol indirect effect, combined with two ocean general circulation models, HYCOM and Russell. Forcings that perturb the model climate during the historical period are described. Five-member ensemble averages from each of the six versions of ModelE2 simulate trends of surface air temperature, atmospheric temperature, sea ice and ocean heat content that are in general agreement with observed trends, although simulated warming is slightly excessive within the past decade. Only simulations that include increasing concentrations of long-lived greenhouse gases match the warming observed during the twentieth century. Differences in twentieth-century warming among the six model versions can be attributed to differences in climate sensitivity, aerosol and ozone forcing, and heat uptake by the deep ocean. Coupled models with HYCOM export less heat to the deep ocean, associated with reduced surface warming in regions of deepwater formation, but greater warming elsewhere at high latitudes along with reduced sea ice. All ensembles show twentieth-century annular trends toward reduced surface pressure at southern high latitudes and a poleward shift of the midlatitude westerlies, consistent with observations.
    Journal of Advances in Modeling Earth Systems 06/2014; 6(2-2):441-477. DOI:10.1002/2013MS000266 · 5.15 Impact Factor
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    ABSTRACT: This study evaluates model simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the AeroCom phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from MODIS, MISR, and SeaWiFS, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based AERONET sunphotometer measurements, and dust vertical distributions/centroid height from CALIOP and AIRS satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects, however the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best-known dust environment, and stresses the need for observable quantities to constrain the model processes.
    Journal of Geophysical Research Atmospheres 05/2014; DOI:10.1002/2013JD021099 · 3.44 Impact Factor
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    ABSTRACT: Though many global aerosols models prognose surface deposition, only a few models have been used to di- rectly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol de- position fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Mod- els (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We ac- complish this by driving the offline land and sea ice com- ponents of the Community Earth System Model with dif- ferent deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measure- ments, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng g−1 for an earlier phase of Aero- Com models (phase I), and +4.1 (−13.0 to +21.4) ng g−1 for a more recent phase of AeroCom models (phase II), com- pared to the observational mean of 19.2 ng g−1. Factors de- termining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, pre- cipitation, deposition efficiency of aerosols within the Arc- tic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90◦ N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, imply- ing large inter-model variation in local BC deposition effi- ciency. Combined with the fact that most Arctic BC depo- sition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07–0.25) W m−2 and 0.18 (0.06–0.28) W m−2 in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different re- gions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m−2 for the combined AeroCom ensembles. Finally, there is a high correlation between mod- eled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.
    Atmospheric Chemistry and Physics 03/2014; 14(5):2399-2417. DOI:10.5194/acp-14-2399-2014 · 4.88 Impact Factor
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    ABSTRACT: Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multimodel-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e. g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
    Atmospheric Chemistry and Physics 01/2014; 14:4679-4713. DOI:10.5194/acp-14-4679-2014 · 4.88 Impact Factor
  • Journal of Advances in Modeling Earth Systems 01/2014; · 5.15 Impact Factor
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    ABSTRACT: This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA/OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a(-1) (range 34-144 Tg a(-1)) and the median SOA source strength (natural and anthropogenic) is 19 Tg a(-1) (range 13-121 Tg a(-1)). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a(-1) (range 16-121 Tg a(-1)), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a(-1); range 13-20 Tg a(-1), with one model at 37 Tg a(-1)). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6-2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8-9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a(-1) (range 28-209 Tg a(-1)), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model-observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model-measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to -0.62 (-0.51) based on the comparison against OC (OA) urban data of all models at the surface, -0.15 (+0.51) when compared with remote measurements, and -0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 01/2014; 14(19). DOI:10.5194/acp-14-10845-2014 · 5.30 Impact Factor
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    ABSTRACT: Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)-Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.
    Atmospheric Chemistry and Physics 12/2013; 14(1). DOI:10.5194/acp-14-427-2014 · 4.88 Impact Factor
  • Susanne E. Bauer, Andrew P. Ault, Kimberly A. Prather
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    ABSTRACT: Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 µm, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 µm contain large fractions of organic material, internally mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.
    Journal of Geophysical Research Atmospheres 09/2013; 118(17):9834-9844. DOI:10.1002/jgrd.50700 · 3.44 Impact Factor
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    ABSTRACT: core measurements in conjunction with climate model simulations are of tremendous value when examining anthropogenic and natural aerosol loads and their role in past and future climates. Refractory black carbon (BC) records from the Arctic, the Antarctic, and the Himalayas are analyzed using three transient climate simulations performed with the Goddard Institute for Space Studies ModelE. Simulations differ in aerosol schemes (bulk aerosols vs. aerosol microphysics) and ocean couplings (fully coupled vs. prescribed ocean). Regional analyses for past (1850-2005) and future (2005-2100) carbonaceous aerosol simulations focus on the Antarctic, Greenland, and the Himalayas. Measurements from locations in the Antarctic show clean conditions with no detectable trend over the past 150 years. Historical atmospheric deposition of BC and sulfur in Greenland shows strong trends and is primarily influenced by emissions from early twentieth century agricultural and domestic practices. Models fail to reproduce observations of a sharp eightfold BC increase in Greenland at the beginning of the twentieth century that could be due to the only threefold increase in the North American emission inventory. BC deposition in Greenland is about 10 times greater than in Antarctica and 10 times less than in Tibet. The Himalayas show the most complicated transport patterns, due to the complex terrain and dynamical regimes of this region. Projections of future climate based on the four CMIP5 Representative Concentration Pathways indicate further dramatic advances of pollution to the Tibetan Plateau along with decreasing BC deposition fluxes in Greenland and the Antarctic.
    Journal of Geophysical Research Atmospheres 07/2013; 118(14):7948-7961. DOI:10.1002/jgrd.50612 · 3.44 Impact Factor
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    ABSTRACT: 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 using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of aerosol indirect effects 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 aerosol indirect effects as low as −5 W m-2 and as high as −0.3 W m-2 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 aerosol indirect effect uncertainty on uncertainty in parameter values.
    Journal of Geophysical Research Atmospheres 06/2013; 118(12). DOI:10.1002/jgrd.50567 · 3.44 Impact Factor
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    ABSTRACT: The impacts of aerosol particles on clouds continue to rank among the largest uncertainties in global climate simulation. In this work we assess the capability of the NASA GISS ModelE, coupled to MATRIX aerosol microphysics, in correctly representing warm-phase aerosol-cloud interactions. This evaluation is completed through the analysis of a nudged, multi-year global simulation using measurements from various US Department of Energy sponsored measurement campaigns and satellite-based observations. Campaign observations include the Aerosol Intensive Operations Period (Aerosol IOP) and Routine ARM Arial Facility Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) at the Southern Great Plains site in Oklahoma, the Marine Stratus Radiation, Aerosol, and Drizzle (MASRAD) campaign at Pt. Reyes, California, and the ARM mobile facility's 2008 deployment to China. This combination of datasets provides a variety of aerosol and atmospheric conditions under which to test ModelE parameterizations. In addition to these localized comparisons, we provide the results of global evaluations completed using measurements derived from satellite remote sensors. We will provide a basic overview of simulation performance, as well as a detailed analysis of parameterizations relevant to aerosol indirect effects.
    06/2013; 118(12):L07-. DOI:10.1002/jgrd.50460
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    ABSTRACT: The impact of black carbon (BC) aerosols on the global radiation balance is not well constrained. Here twelve global aerosol models are used to show that at least 20 % of the present uncertainty in modeled BC direct radiative forc-ing (RF) is due to diversity in the simulated vertical profile of BC mass. Results are from phases 1 and 2 of the global aerosol model intercomparison project (AeroCom). Addi-tionally, a significant fraction of the variability is shown to come from high altitudes, as, globally, more than 40 % of the total BC RF is exerted above 5 km. BC emission regions and areas with transported BC are found to have differing char-acteristics. These insights into the importance of the vertical profile of BC lead us to suggest that observational studies are needed to better characterize the global distribution of BC, including in the upper troposphere.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 03/2013; 13(5):2423-2434. DOI:10.5194/acp-13-2423-2013 · 5.30 Impact Factor
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    ABSTRACT: 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 bio-fuel 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.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 02/2013; 13(4):1853-1877. DOI:10.5194/acp-13-1853-2013 · 5.30 Impact Factor
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    ABSTRACT: Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea-ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea-ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004-2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are -4.4 (-13.2 to +10.7) ng g-1 for an earlier Phase of AeroCom models (Phase I), and +4.1 (-13.0 to +21.4) ng g-1 for a more recent Phase of AeroCom models (Phase II), compared to the observational mean of 19.2 ng g-1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90° N) atmospheric residence time for BC in Phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W m-2 and 0.18 (0.06-0.28) W m-2 in Phase I and Phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m-2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.
    Atmospheric Chemistry and Physics 01/2013; 13(10):26217-26267. DOI:10.5194/acpd-13-26217-2013 · 4.88 Impact Factor
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    ABSTRACT: The impact of black carbon (BC) aerosols on the global radiation balance is not well constrained. Here twelve global aerosol models are used to show that at least 20% of the present uncertainty in modeled BC direct radiative forcing (RF) is due to diversity in the simulated vertical profile of BC mass. Results are from phases 1 and 2 of the global aerosol model intercomparison project (AeroCom). Additionally, a significant fraction of the variability is shown to come from high altitudes, as, globally, more than 40% of the total BC RF is exerted above 5 km. BC emission regions and areas with transported BC are found to have differing characteristics. These insights into the importance of the vertical profile of BC lead us to suggest that observational studies are needed to better characterize the global distribution of BC, including in the upper troposphere.
    Atmospheric Chemistry and Physics 01/2012; DOI:10.5194/acpd-12-28929-2012 · 4.88 Impact Factor

Publication Stats

3k Citations
289.19 Total Impact Points

Institutions

  • 2006–2014
    • Columbia University
      • • Center for Climate Systems Research
      • • Earth Institute
      New York, New York, United States
  • 2009–2013
    • NASA
      Вашингтон, West Virginia, United States
    • University of Oslo
      • Department of Geosciences
      Kristiania (historical), Oslo, Norway
  • 2008–2012
    • Space Studies Institute
      Mojave, California, United States
  • 2007
    • Lamont - Doherty Earth Observatory Columbia University
      New York, New York, United States
  • 2004
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France