S. E. Bauer

Columbia University, New York City, New York, United States

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Publications (69)270.31 Total impact

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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 05/2014; · 3.17 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; 14:2399-2417. · 4.88 Impact Factor
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    Atmospheric Chemistry and Physics 01/2014; 14:4679-4713. · 4.88 Impact Factor
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    Journal of Advances in Modeling Earth Systems 01/2014; 6(2):441-477. · 4.11 Impact Factor
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    ATMOSPHERIC CHEMISTRY AND PHYSICS 01/2014; · 5.51 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 01/2014; · 3.17 Impact Factor
  • Journal of Advances in Modeling Earth Systems 01/2014; · 4.11 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). · 4.88 Impact Factor
  • Susanne E. Bauer, Andrew 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 09/2013; 118(17):9834-9844. · 3.17 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 07/2013; 118(14):7948-7961. · 3.17 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 06/2013; · 3.17 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 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; 13:2423-2434. · 5.51 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; 13:1853-1877. · 5.51 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. · 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; · 4.88 Impact Factor
  • Susanne E. Bauer, Surabi Menon
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    ABSTRACT: The anthropogenic increase in aerosol concentrations since preindustrial times and its net cooling effect on the atmosphere is thought to mask some of the greenhouse gas-induced warming. Although the overall effect of aerosols on solar radiation and clouds is most certainly negative, some individual forcing agents and feedbacks have positive forcing effects. Recent studies have tried to identify some of those positive forcing agents and their individual emission sectors, with the hope that mitigation policies could be developed to target those emitters. Understanding the net effect of multisource emitting sectors and the involved cloud feedbacks is very challenging, and this paper will clarify forcing and feedback effects by separating direct, indirect, semidirect and surface albedo effects due to aerosols. To this end, we apply the Goddard Institute for Space Studies climate model including detailed aerosol microphysics to examine aerosol impacts on climate by isolating single emission sector contributions as given by the Coupled Model Intercomparison Project Phase 5 (CMIP5) emission data sets developed for Intergovernmental Panel on Climate Change (IPCC) AR5. For the modeled past 150 years, using the climate model and emissions from preindustrial times to present-day, the total global annual mean aerosol radiative forcing is -0.6 W/m2, with the largest contribution from the direct effect (-0.5 W/m2). Aerosol-induced changes on cloud cover often depends on cloud type and geographical region. The indirect (includes only the cloud albedo effect with -0.17 W/m2) and semidirect effects (-0.10 W/m2) can be isolated on a regional scale, and they often have opposing forcing effects, leading to overall small forcing effects on a global scale. Although the surface albedo effects from aerosols are small (0.016 W/m2), triggered feedbacks on top of the atmosphere (TOA) radiative forcing can be 10 times larger. Our results point out that each emission sector has varying impacts by geographical region. For example, the single sector most responsible for a net positive radiative forcing is the transportation sector in the United States, agricultural burning and transportation in Europe, and the domestic emission sector in Asia. These sectors are attractive mitigation targets.
    Journal of Geophysical Research 01/2012; 117(D1):1206-. · 3.17 Impact Factor
  • S. E. Bauer, K. A. Prather, A. P. Ault
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    ABSTRACT: Aerosol particles in the atmosphere are composed out of multiple chemical species. The aerosol mixing state is an important aerosol property that will determine the interaction of aerosols with the climate system via radiative forcings and cloud activation. Through the introduction of aerosol microphysics into climate models, aerosol mixing state is by now taken into account to a certain extend in climate models, and evaluation of mixing state is the next challenge. Here we use data from the Aerosol Time of Flight Mass Spectrometer (ATOFMS) and compare the results to the GISS-modelE-MATRIX model, a global climate model including a detailed aerosol micro-physical scheme. We use data from various field campaigns probing, urban, rural and maritime air masses and compare those to climatological and nudged simulations for the years 2005 to 2009. ATOFMS provides information about the size distributions of several mixing state classes, including the chemical components of black and organic carbon, sulfates, dust and salts. MATRIX simulates 16 aerosol populations, which definitions are based on mixing state. We have grouped ATOFMS and MATRIX data into similar mixing state classes and compare the size resolved number concentrations against each other. As a first result we find that climatological simulations are rather difficult to evaluate with field data, and that nudged simulations give a much better agreement. However this is not just caused by the better fit of natural - meteorological driven - aerosol components, but also due to the interaction between meteorology and aerosol formation. The model seems to get the right amount of mixing state of black carbon material with sulfate and organic components, but seems to always overestimate the fraction of black carbon that is externally mixed. In order to understand this bias between model and the ATOFMS data, we will look into microphysical processes near emission sources and investigate the climate relevance of these sub-grid scale mixing processes.
    AGU Fall Meeting Abstracts. 12/2011;

Publication Stats

2k Citations
270.31 Total Impact Points

Institutions

  • 2006–2014
    • Columbia University
      New York City, New York, United States
  • 2008–2013
    • Space Studies Institute
      Mojave, California, United States
  • 2009
    • NASA
      Washington, West Virginia, United States
  • 2004
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France