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Section 5. Tropospheric aerosols

5.5. Increases in aerosol model complexity – 2nd generation models: 2010s

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As aerosol modelling matured, further refinements of aerosol direct and indirect effects were

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included in GCMs. Further components of aerosol were included; Bellouin et al (2011) included

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nitrate aerosol and pointed out that as sulphur dioxide emissions decrease in the future owing to

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emission control, the radiative forcing of nitrate will likely increase owing to the availability of

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excess ammonia in the atmosphere. However, nitrate continues to remain a difficult aerosol to

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model owing to the dissociation to nitric acid and ammonia under ambient temperature and

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humidities.

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The development of aerosol mass spectrometers and their location at surface sites and airborne

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platforms enabled, for the first time, a full appreciation of the complexity of optically active sub-

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micron aerosol composition as a function of location and altitude to be deduced (Jimenez et al.,

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2011) with sulphate, organic and nitrate highlighted as the dominant sub-micron components. The

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problems of the mutual exclusivity of satellite-retrievals of aerosol and cloud can be avoided using

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active satellite sensors such as CALIPSO lidar aerosol data collocated with MODIS cloud data

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(e.g. Costantino and Bréon, 2013). However,in-situ airborne platforms with dedicated

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instrumentation such as nephelometers, and aerosol optical particle counters continued to provide

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vital information on the aerosol vertical profiles at a level of detail and vertical resolution

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impossible to achieve with satellite mounted lidars.

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2349 2350

In modelling, dual-moment schemes became more common, treating both aerosol number and

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aerosol mass prognostically (Stier et al., 2005) and both internal and external mixtures. This has

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particular relevance to estimates of aerosol-cloud-interactions because, for single-moment

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schemes with prognostic mass only, any increase in the aerosol mass (e.g. via condensation or

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coagulation), must artificially increase the aerosol number and hence CCN which then produces

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stronger aerosol indirect effects. The use of dual-moment state-of-the-art aerosol schemes in

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GCMs is now common-place.

2357 2358

Lohmann et al. (2010) examined the differences between i) the radiative flux perturbation (RFP;

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Haywood et al., 2009) which is calculated as the difference in the top-of-the-atmosphere

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radiation budget between a present-day simulation and a preindustrial simulation, both using the

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same sea surface temperatures and ii) the radiative forcing computed from two–calls to the

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radiative transfer code in GCMs holding the atmospheric state fixed. The RFP calculation allows

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for rapid responses (e.g. in clouds), that occur on a faster time-scale than the large-scale shifts in

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climate response thaare induced through SST responses. RFP has become more commonly

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known as the effective radiative forcing (ERF – see Section 2.3.6). Allowing rapid adjustment to

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occur in diagnosing the ERF allowed isolation of both the Twomey (1977) and the Albrecht

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(1989) aerosol indirect effects and also aerosol semi-direct effects.

2368 2369

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Myhre (2009) suggested that the discrepancy between observational (stronger) and modelled

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(weaker) estimates of aerosol direct forcing highlighted in IPCC (2007) was due to the lack of

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account of aerosol absorption above clouds and (ii) relatively larger fractional increase in BC

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containing absorbing than scattering aerosols since pre-industrial times. Analysis of models

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reported an aerosol direct radiative forcing of -0.3W m-2 which was found to be consistent with

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observational estimates. Aerosol absorption was again highlighted as a major uncertainty in

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accurate determination of aerosol direct radiative forcing (Bond et al., 2013) owing to aspects such

2378

as the morphology of the black carbon as a function of age and the impact of coatings of organic

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and inorganic components, the heating in the atmospheric column and subsequent rapid

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adjustment. Again this suggested that diagnosing the radiative forcing in a strict sense could not

2381

capture the rapid adjustment associated with atmospheric processes.

2382 2383

Boucher et al. (2013), Myhre et al (2013) and IPCC (2013) recognized that retaining the strict

2384

definition of radiative forcing as in previous IPCC reports was becoming untenable because it

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did not reflect the growing consensus that rapid responses can and should be isolated in any

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metric ofclimate change, but also because of the ease of application to GCM simulations. Hence

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the growth of ERF as the preferred metric for assessing potential climate impacts. Indeed, IPCC

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also chose the term aerosol-radiation-interactions over the aerosol direct forcing and aerosol-

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cloud interactions over aerosol indirect with rapid adjustment of aerosol-radiation interaction as a

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term for the semi-direct effect (Boucher et al., 2013). By this time there were many mature

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estimates of the impact of aerosol-radiation-interactions and aerosol-cloud-interactions from

sophisticated GCMs and satellite-based estimates (e.g. Fig 5.3; see also Table 7.4 and 7.5 of

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Boucher et al. , 2013) allowing Myhre et al (2013) to estimate the magnitude of pre-industrial to

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present-day aerosol-radiation-interactions (-0.45W m-2 with a 95% uncertainty range of -0.9 to

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+0.05W m-2)and aerosol-cloud-interactions (-0.45W m-2 with a 95% uncertainty range of -1.2

2396 to 0 W m-2). 2397 2398 2399 2400

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