Top PDF Global distribution and climate forcing of marine organic aerosol: 1. Model improvements and evaluation

Global distribution and climate forcing of marine organic aerosol: 1. Model improvements and evaluation

Global distribution and climate forcing of marine organic aerosol: 1. Model improvements and evaluation

cally inactive regions to hundreds per cm 3 under biologi- cally active conditions (Andreae, 2007). Thus, factors that regulate the concentration of marine aerosols and the result- ing reflectivity of low-level marine clouds can critically af- fect the climate system as a whole (e.g. Randall et al., 1984; Stevens et al., 2005). Despite their importance, the source strength and chemical composition of marine aerosols re- main poorly quantified (O’Dowd and de Leeuw, 2007; An- dreae and Rosenfeld, 2008). Therefore, most modeling stud- ies that have attempted to simulate the atmosphere before the advent of humans do not represent natural marine aerosols realistically. Instead, to compensate for missing natural ma- rine aerosol sources, global aerosol-climate models impose lower bounds on CDNC or aerosol number concentration over remote marine areas (Lohmann et al., 1999, 2007; Take- mura et al., 2005; Wang and Penner, 2009). When these possibly unphysical constraints are removed, the simulated aerosol indirect effect can change by up to 80 % (Kirkev˚ag et al., 2008; Hoose et al., 2009). Changes of this magni- tude can have profound effects on the model-predicted extent of human-induced climate change and highlight the need for improved modeling of marine aerosol number size distribu- tion and chemical composition over pristine marine regions. Natural aerosols over remote oceanic regions consist mainly of a mixture of sea-salt particles, organics, and sul- fates from the oxidation of biogenic dimethyl sulfide (DMS) with contributions from mineral dust and smoke from wild- fires in some regions (Andreae, 2007). Sea-salt has been proposed to be a major component of marine aerosol over the regions where wind speeds are high and/or other aerosol sources are weak (O’Dowd et al., 1997; Murphy et al., 1998; Quinn et al., 1998). At typical wind speeds encountered during the cruises, sea-salt have been shown to be present in aerosol from 10 nm to several micrometers in diameter with a total number concentration above 100 cm −3 (Geever et al., 2005; Clarke et al., 2006; Smith, 2007). Using a cou- pled global aerosol-climate model with a size-resolved sea- salt aerosol parameterization, Ma et al. (2008) estimated that global direct and first indirect radiative forcings associated with sea-salt aerosol were −0.60 W m −2 and −1.34 W m −2 , respectively.
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Global distribution and climate forcing of marine organic aerosol – Part 1: Model improvements and evaluation

Global distribution and climate forcing of marine organic aerosol – Part 1: Model improvements and evaluation

Neale, R. B., Chen, C.-C., Gettelman, A., Lauritzen, P. H., Park, S., Williamson, D. L., Con- ley, A. J., Garcia, R., Kinnison, D., Lamarque, J.-F., Marsh, D., Mills, M., Smith, A. K., Tilmes, S., Vitt, F., Cameron-Smith, P., Collins, W. D., Iacono, M. J., Easter, R. C., Ghan, S. J., Liu, X., Rasch, P. J., and Taylor, M. A.: Description of the NCAR Community Atmosphere Model (CAM 5.0), NCAR technical note, 2010.

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Global distribution and radiative forcing of soil dust aerosols in the Last Glacial Maximum simulated by the aerosol climate model

Global distribution and radiative forcing of soil dust aerosols in the Last Glacial Maximum simulated by the aerosol climate model

Braconnot, P., Otto-Bliesner, B., Harrison, S., Joussaume, S., Peterchmitt, J.-Y., Abe-Ouchi, A., Crucix, M., Driesschaert, E., Fichefet, Th., Hewitt, C. D., Kageyama, M., Kitoh, A., Laˆın ´e, A., Loutre, M.-F., Marti, O., Merkel, U., Ramstein, G., Valdes, P., Weber, S. L., Yu, Y., and Zhao, Y.: Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum – Part 1: experiments and large-scale features, Clim. Past, 3, 261–277, 2007,

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A global model simulation of present and future nitrate aerosols and their direct radiative forcing of climate

A global model simulation of present and future nitrate aerosols and their direct radiative forcing of climate

Figure 7 shows the calculated total aerosol optical depth at 550 nm and the optical depth associated with fine and coarse nitrate particles. The total aerosol optical depth (AOD) ex- hibits values of 0.15–0.25 over the eastern United States and Europe, associated mostly with pollution aerosols. Maxi- mum values reaching more than 0.5 and associated with dust aerosols are calculated over northern Africa, Saudi Arabia, and China. In China, both natural and pollution aerosols con- tribute to the high aerosol optical depth. Distributions very similar to these results have also been presented in other studies (e.g., Kinne et al., 2006; Bellouin et al., 2011; Xu and Penner, 2012; Shindell et al., 2013). The global mean and total AOD is 0.135, with accumulation-mode particles contributing 0.059 to AOD. As expected from the burden shown in Figure 3, nitrates exhibit higher optical depth over source regions: values of 0.02–0.03 over the central United States, maximum optical depth of 0.05 in northern Europe, and more than 0.1 in northern China. The contribution of ni- trates formed from biomass burning emissions is also vis- ible in South America, Africa, and Indonesia, with values reaching 0.1 in the later region. The nitrate optical depth is in good agreement with the results presented by Myhre et al. (2006) regarding both the general patterns of the distribu- tion and the calculated values. The global mean and total ni- trate optical depth is 0.0053. Fine nitrate particles contribute 0.0048 to this total number. The evaluation of the calculated total AOD by comparing with the measurements from the Aerosol Robotic Network (AERONET) network (Holben et al., 2001, Kinne et al., 2006) is summarized in Table 2 (see Supplement for individual plots). Matching daily data from the model and AERONET were aggregated to monthly av- erages. Worldwide, the measured and modeled AOD show a relatively good correlation (R = 0.57). The arithmetic mean for the measurements of 0.226 is, however, underestimated by the modeled values of 0.202 with a normalized mean bias (NMB) of −11 %. A good agreement with the AERONET measurements is obtained over North America. Over this re- gion, the model slightly underestimates the measurements (NMB = −4.5 %, R = 0.77). Over Africa, higher AOD as- sociated with dust aerosols are calculated. A fairly good cor- relation is reached (R = 0.66), also with a light underesti- mate by the model of −10 %. Over eastern Asia, the model underestimates the AOD (NMB = −39 %). Over Europe, a fairly good correlation between model and measurement is obtained (R = 0.58). However, over this region, the model overestimates the measurements (NMB = +6 %).
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Sensitivity of aerosol concentrations and cloud properties to nucleation and secondary organic distribution in ECHAM5-HAM global circulation model

Sensitivity of aerosol concentrations and cloud properties to nucleation and secondary organic distribution in ECHAM5-HAM global circulation model

J., Lowe, D.C., Myhre, G., Nganga, J., Prinn, R., Raga, G., Schulz, M., and Van Dorland, R.: Changes in Atmospheric Constituents and in Radiative Forcing, in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B.,Tignor, M., and Miller, H. L., Cambridge

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The AeroCom evaluation and intercomparison of organic aerosol in global models

The AeroCom evaluation and intercomparison of organic aerosol in global models

In Alaska, USA (Fig. 21), many models simulate a sum- mer maximum, in agreement with the measurements; this is due to biomass burning sources. TM4-ECPL-FNP calculates a very strong contribution from primary biological particles to the total OC, resulting in a slight overestimation of mea- surements throughout the year. The four models that have provided mPOA concentrations (two GISS-modelE and two TM4-ECPL models) suggest that marine organics are present in significant quantities. Multiphase chemistry is also cal- culated to contribute during the summer months. ECMWF- GEMS shows a very wide peak in OC during summer, in contrast with the other models, resulting in higher concentra- tions than the measured ones for half of the year. This might be caused by the averaging of biomass burning emissions over six fire seasons that this model uses, which exhibit a large interannual variability and which broaden the biomass burning contribution over many months. The remaining mod- els generally underestimate the measurements, although they capture the observed seasonality rather well; more than half of the models have a correlation coefficient against measure- ments greater than 0.8. An interesting pattern is that of the two GISS-modelE models, which simulate a significant con- tribution of trSOA to the total OC, especially during win- ter. These two models are the only models that include semi- volatile SOA, and use the Lathière et al. (2005) VOC emis- sions, in which strong summer emissions in southern Alaska are present (Tsigaridis et al., 2005). It is very likely that the distribution of VOC sources (which differs from that of the other models), when combined with the low temperatures
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Modeling of 2008 Kasatochi volcanic sulfate direct radiative forcing: assimilation of OMI SO<sub>2</sub> plume height data and comparison with MODIS and CALIOP observations

Modeling of 2008 Kasatochi volcanic sulfate direct radiative forcing: assimilation of OMI SO<sub>2</sub> plume height data and comparison with MODIS and CALIOP observations

The MODIS aerosol optical depth (AOD) product is used to validate our simulation of volcanic sulfate aerosol. The MODIS instruments aboard NASA’s Terra and Aqua satel- lites provide near daily global coverage at their local equato- rial overpass times of 10:30 a.m. and 1:30 p.m., respectively (Remer et al., 2005). Since MODIS AOD is a columnar quan- tity that has limited information about the aerosol chemical composition and aerosol vertical distribution, a direct com- parison between MODIS AOD and the modeled volcanic sulfate AOD is not straightforward, in particular when other types of aerosols dominate in the atmospheric column. How- ever, over remote regions where background AOD is gen- erally low, the spatial distribution of high MODIS AOD is still expected to be a good indicator of the transport path or distribution of volcanic aerosol. Hence, we use MODIS AOD for the evaluation of model-simulated transport pathways and distributions (instead of the absolute amount) of volcanic sul- fate aerosol. For this purpose, we use the MODIS level 3 AOD product (from both Terra and Aqua) with a spatial res- olution of 1 ◦ × 1and an uncertainty of ±0.05 AOD ±0.03 over the ocean and ±0.20 AOD ±0.05 over the land (Remer et al., 2005).
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Aerosol size distribution and radiative forcing response to anthropogenically driven historical changes in biogenic secondary organic aerosol formation

Aerosol size distribution and radiative forcing response to anthropogenically driven historical changes in biogenic secondary organic aerosol formation

There are also increases in N80 over oceanic regions downwind of regions with significant decreases in N80. This is caused by the increases in N3 and N10 over land. When the air mass is advected over the ocean, the surplus of small particles are able to grow via condensation to CCN sizes. Figure 5 shows the zonal-mean percentage change in (a) N3, (b) N10, (c) N40, and (d) N80 when changing MEGAN BVOC emissions from year 1000 to year 2000 with constant present-day anthropogenic emissions (2005) (BE2.AE2.meg–BE1.AE2.meg). Figure 5 indicates that the difference in number concentrations between the two sim- ulations varies with height. The difference in N3 and N10 between the simulations with height generally remains pos- itive above the boundary layer (BL), with increases exceed- ing 5 % in the southern mid-latitudes in oceanic and defor- ested regions particularly. However, the differences in N40 and N80 between the simulations reverse sign with height in the mid-latitudes, most dramatically in the Southern Hemi- sphere such that there are more particles in the BE2.AE2.meg simulation. When CCN-sized particles are removed through wet deposition during vertical advection, there are more ul- trafine particles to grow to CCN sizes and replace the lost CCN in the BE2.AE2.meg simulation than in BE1.AE2.meg. This feedback leads to the change in sign with height for N40 and N80. This reversal in the change in particle number con- centrations has implications for radiative forcing and will be discussed in Sect. 4.3.
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A secondary organic aerosol formation model considering successive oxidation aging and kinetic condensation of organic compounds: global scale implications

A secondary organic aerosol formation model considering successive oxidation aging and kinetic condensation of organic compounds: global scale implications

The contribution of secondary organic aerosol (SOA) to par- ticle growth, size, and mass is one of the major uncertain- ties in current regional and global aerosol simulations. The volatility changes of secondary organic gases (SOGs) aris- ing from the aging process as well as the contribution of low volatile SOGs to the condensational growth of secondary particles have been found to be important in recent labora- tory and field measurements but are poorly represented in global aerosol models. In this study, we extend the widely used N × 2p SOA formation model so that it can consider the aging process as well as the kinetic condensation of low- volatile SOGs (i.e., N × 2p + A/C). According to their effec- tive saturation vapor pressure, we group SOGs from bio- genic VOC oxidation into two classes: semi-volatile SOG (SV-SOG) and medium-volatile SOG (MV-SOG). There- after, we extend the N × 2p model by adding a third com- ponent representing low-volatile SOG (LV-SOG) and design a scheme to transfer MV-SOG to SV-SOG and SV-SOG to LV-SOG as a result of oxidation aging. The saturation va-
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Tropospheric aerosol microphysics simulation with assimilated meteorology: model description and intermodel comparison

Tropospheric aerosol microphysics simulation with assimilated meteorology: model description and intermodel comparison

Barrie, L. A., Yi, Y., Leaitch, W. R., Lohmann, U., Kasibhatla, P., Roelofs, G. J., Wilson, J., McGovern, F., Benkovitz, C., Melieres, M. A., Law, K., Prospero, J., Kritz, M., Bergmann, D., Bridgeman, C., Chin, M., Christensen, J., Easter, R., Feichter, J., Land, C., Jeuken, A., Kjellstrom, E., Koch, D., and Rasch, P.: A comparison of large-scale atmospheric sulphate aerosol models (COSAM): overview and highlights, Tellus B, 53, 615–645, 2001.

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Aerosol size distribution and radiative forcing response to anthropogenically driven historical changes in biogenic secondary organic aerosol formation

Aerosol size distribution and radiative forcing response to anthropogenically driven historical changes in biogenic secondary organic aerosol formation

(see Table 2). The spatial distribution of the global changes in particle number concen- trations are similar to those of Fig. 4, with modest increases in magnitude. Even with more than a doubling of the SOA yields from all three terpenoid species, the change in particle number responded with less than a doubling due to microphysical damp- ening. This has also been observed in other global aerosol microphysics models (e.g.

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The effect of harmonized emissions on aerosol properties in global models – an AeroCom experiment

The effect of harmonized emissions on aerosol properties in global models – an AeroCom experiment

A brief overview of the AeroCom models including a table linking model name abbreviations to the model versions ac- tually used can be found in Table 1, a comprehensive de- scription is given in T2006. The model configurations did not change between ExpA and ExpB, except for three mod- els: In the DLR model, coarse aerosols have been added only in ExpB. Larger changes have been made in KYU, where the interaction between aerosols and clouds has been included for ExpB, and carbonaceous aerosols (BC and POM) are treated externally, unlike the internal treatment in ExpA. In LOA, dry turbulent deposition is only considered in ExpA. In addition, deviations from the recommended AeroCom emis- sions occurred: In KYU and UIO GCM, sources of DU and SS remained those of ExpA. For the fine aerosols in KYU, only the emitted aerosol mass flux was matched, but size distributions have not been adapted. In ARQM, emis- sions have been modified for ExpB, but did not follow the ExpB recommendations. In MATCH, SS sources remained those of ExpA. Due to these deviations, all results of DLR, KYU, LOA, ARQM, as well as UIO GCM, and the SS and AER results of MATCH are discussed, but not included in the calculation of the model diversities. We also discard the results for all species in UIO GCM, although the emis- sions of BC, POM, and the sulfur species are consistent with the AeroCom ExpB recommandations. However, interac- tions among different aerosol types are taken into account in UIO GCM, because internal aerosol mixtures are con- sidered. Therefore, the results of all species are influenced by the non-AeroCom emissions of SS and DU. This is, by contrast, not the case in MATCH. Hence, we include GISS, LSCE, MATCH, MOZGN, UIO CTM, ULAQ and UMI in the statistics, MATCH is excluded from the calculations for SS and AER. The models that are excluded from the statis- tics are shaded in gray in the figures. Due to our sampling procedure, the statistics on ExpA reported in this paper do not entirely match the results reported in T2006.
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A review of measurement-based assessments of the aerosol direct radiative effect and forcing

A review of measurement-based assessments of the aerosol direct radiative effect and forcing

and ocean. On a global annual average, the cloud fraction is about 0.63 and cloud optical depth is 10.8. Compared with clouds over ocean, clouds over land are optically thicker and have smaller cloud fraction. While the combination of MODIS/Terra and MODIS/Aqua allows for some indi- cation of cloud evolution from late morning to early after- noon, the International Satellite Cloud Climatology Project (ISCCP) has been providing diurnal variations of clouds for two decades (Schiffer and Rossow, 1983; Rossow and Schif- fer, 1991, 1999). Such information can be exploited to better constrain the estimate of the aerosol direct effect in cloudy sky conditions (in terms of diurnal variation of clouds) and to study interannual variations of the aerosol radiative effect. However satellite cloud retrievals have significant uncer- tainties and biases, resulting from cloud heterogeneity, as- sumption on the size distribution, and inadequacy of ac- counting for surface and aerosol contributions to the re- flectance, among others. These uncertainties/biases are sensor dependent and cross-platform comparisons generally show both consistence/correlation and discrepancies (Br´eon and Doutriaux-Boucher, 2005; Mahesh et al., 2004). A plane-parallel approximation would result in a high bias in the effective radius for convective clouds with a great het- erogeneity (e.g., Kaufman and Nakajima, 1993; Platnick and Valero, 1995; Reid et al., 1999). Exclusion of aerosols in the cloud retrieval algorithm could result in low biases in cloud optical depth (as large as -30%) and effective radius (as large as −3 µm) in cases of smoke overlaid low-level clouds (Haywood et al., 2004). The low bias of cloud droplet ef- fective radius, hence the high bias in cloud reflectivity, could underestimate the TOA DRE by ∼4%, while the low bias of cloud optical depth could overestimate the TOA DRE by 26% (Abel et al., 2004). Heavy aerosols may be misclassi- fied as clouds (Brennan et al., 2005), which could introduce additional uncertainties in cloud retrievals. Profiling clouds from space is far from adequate. MODIS and AVHRR can detect cloud top but not cloud base. Spaceborne lidar such as GLAS and CALIOP has a capability of measuring the ex- tinction profile of optically thin clouds (e.g., cloud optical depth <3). Such profiling is not possible for optically thick clouds, although the cloud top and base could be located through holes and edges of broken clouds (Spinhirne, et al., 2005). CloudSat, scheduled to be launched in 2006, will use radar to survey the vertical structure of cloud systems glob- ally, including liquid and water content profile (Stephens et al., 2002).
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Carlos Carvalho Niels Arne Dam Jae Won Lee

Carlos Carvalho Niels Arne Dam Jae Won Lee

Before we continue, a brief digression about the Taylor pricing model is in order. As will become clear, this model allows us to tell apart real rigidities from nominal rigidities, and to infer the cross- sectional distribution of price stickiness implied by aggregate data. Hence, it serves our purposes well. However, strictly speaking, that model is at odds with the microeconomic evidence on the duration of price spells. Klenow and Kryvtsov (2008), for example, provide evidence that the duration of individual price spells varies at the quote line level. However, this evidence does not invalidate the use of the Taylor model for our purposes. In particular, in Section 5 we provide an alternative model in which the duration of price spells varies at the …rm level, and yet the aggregate behavior of the model is identical to the one presented here. The alternative model can match additional micro facts documented in the literature. Hence, it provides a cautionary note on attempts to test speci…c models of price setting by confronting them with descriptive micro price statistics. For ease of exposition, we proceed with the standard Taylor pricing speci…cation. But the reader should keep in mind that the aggregate implications that we are interested survive in models that can match the microeconomic evidence in many dimensions.
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The relationship between aerosol and cloud drop number concentrations in a global aerosol microphysics model

The relationship between aerosol and cloud drop number concentrations in a global aerosol microphysics model

persaturation. For example, Kristjansson (2002) prescribe a constant S max in all strati- form and all convective clouds (also used by Kristjansson et al., 2005; Kirkevag et al., 2008). With a globally uniform updraft velocity, the maximum supersaturation attained in a rising air parcel varies throughout the globe as high aerosol loadings can sup- press S max . Thus in a polluted region, a smaller fraction of the available CCN will

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Simultaneous Determination Of Adjusted Ranks Of Sample Observations And Their Sums And Products

Simultaneous Determination Of Adjusted Ranks Of Sample Observations And Their Sums And Products

The above procedure would easily enable one systematically assign ranks to sampled observations drawn from a given population whether or not there are tied observations and simultaneously estimate the sum and mean of these ranks. Similarly, the method enables one to easily obtain more efficient estimates of the sum of squares and cross products of ranks of sample observations whether or not some or all of the observations are tied in values and hence assigned mean ranks. With these results, one may now proceed to estimate some ties adjusted statistics. For example, one may estimate ties adjusted Spearman rank correlation coefficient between pairs of observations drawn from populations X 1 and X 2 .
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A global modeling study on carbonaceous aerosol microphysical characteristics and radiative forcing

A global modeling study on carbonaceous aerosol microphysical characteristics and radiative forcing

into several size bins. These choices differed greatly among the models; furthermore there is very little information available about actual emission sizes. Bond et al. (2006, Table 3.) collected particle size distribution observations at combustion sources from the literature and reported mass median diameters of 0.038–0.32 µm for diesel vehi- cles, 0.02–1.5 µm for gasoline vehicles, 0.1–1.3 µm for small solid fuel combustors (ex-

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Black carbon reduction will weaken the aerosol net cooling effect

Black carbon reduction will weaken the aerosol net cooling effect

warming could be slowed down in a short term by eliminating BC emission due to its short lifetime. In this study, we estimate the influence of removing some sources of BC and other co-emitted species on the aerosol radiative effect by using an aerosol-climate coupled model BCC_AGCM2.0.1_CUACE/Aero, in combination with the aerosol emis- sions from the Representative Concentration Pathways (RCPs) scenarios. We find that

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Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

National Center for Atmospheric Research is operated by the Uni- versity Corporation for Atmospheric Research under sponsorship of the National Science Foundation. The work of DB and PC was funded by the US Dept. of Energy (BER), performed under the aus- pices of LLNL under Contract DE-AC52-07NA27344, and used the supercomputing resources of NERSC under contract No. DE- AC02-05CH11231. VN and LWH acknowledge efforts of GFDL’s Global Atmospheric Model Development Team in the develop- ment of the GFDL-AM3 and Modeling Services Group for assis- tance with data processing. The GEOSCCM work was supported by the NASA Modeling, Analysis and Prediction program, with com- puting resources provided by NASA’s High-End Computing Pro- gram through the NASA Advanced Supercomputing Division. The MIROC-CHEM calculations were perfomed on the NIES super- computer system (NEC SX-8R), and supported by the Environment Research and Technology Development Fund (S-7) of the Ministry of the Environment, Japan. The STOC-HadAM3 work made use of the facilities of HECToR, the UK’s national high-performance com- puting service, which is provided by UoE HPCx Ltd at the Univer- sity of Edinburgh, Cray Inc and NAG Ltd., and funded by the Office of Science and Technology through EPSRC’s High End Comput- ing Programme. The LMDz-OR-INCA simulations were done us- ing computing resources provided by the CCRT/GENCI computer center of the CEA. The CICERO-OsloCTM2 simulations were done within the projects SLAC (Short Lived Atmospheric Compo- nents) and EarthClim funded by the Norwegian Research Council. The MOCAGE simulations were supported by M´et´eo-France and CNRS. Supercomputing time was provided by M´et´eo-France/DSI supercomputing center. DTS and YHL acknowledge support from the NASA MAP and ACMAP programs. D. P. would like to thank the Canadian Foundation for Climate and Atmospheric Sciences for their long-running support of CMAM development. AC was sup- ported by the SciDAC program of the Dept. of Energy.
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Implementing marine organic aerosols into the GEOS-Chem model

Implementing marine organic aerosols into the GEOS-Chem model

and for providing boundary conditions to regional chemical transport models (CTMs). Global emissions estimates of marine POA and inter-comparison of multiple emission parameterizations has been previously performed using older versions of GEOS-Chem (Spracklen et al., 2008; Lapina et al., 2011; Gantt et al., 2012); these studies had vari- able success replicating the observed surface organic aerosol concentrations in clean

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