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Apoyo familiar como modo adaptativo de interdependencia

RESULTADOS Y DISCUSIÓN

4. Apoyo familiar como modo adaptativo de interdependencia

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Stratospheric aerosols, both volcanic and background, scatter the incoming shortwave

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radiation depleting the direct and enhancing the diffuse downward solar fluxes; they also

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absorb shortwave near infrared, and absorb and emit outgoing terrestrial radiation. The

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cumulative radiative effect of stratospheric aerosols is to cool the Earth’s surface and heat

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the aerosol layer in the lower stratosphere.

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Volcanic eruptions that have historically exerted the strongest radiative forcing, have i)

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significant SO2/H2S injected into the stratosphere (although there is growing evidence of

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non-linearity of injections strength and radiative forcing (e.g. Niemeier and Tilmes, 2017) ,

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ii) tend to occur in tropical regions where both hemispheres of the globe are impacted by the

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subsequent perturbation to the aerosol optical depth and iii) inject SO2 to sufficiently high

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altitudes within the stratosphere (e.g. Jones et al., 2017).

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The large perturbations of the Earth’s radiative balance caused by explosive volcanic

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eruptions e.g., Pinatubo, are discernible in observations; however, this does not lend itself

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readily to quantifying their actual radiative forcing (Dutton and Christy, 1992; Minnis et al.,

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1993; Russell et al., 1993). The theoretical calculations of the radiative forcing of

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stratospheric aerosols were first attempted using conceptual models (Lacis et al., 1992;

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Harshvardhan, 1979; Toon and Pollack, 1976). Because aerosol microphysical and optical

characteristics, which have to be compiled from observations or calculated within the

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model, are the major input into the radiative forcing calculations, we discuss both these

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aspects together here.

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The first generation of the atmospheric general circulation models simulated the impact of

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volcanic aerosols using simplified approaches, i.e., assuming a reduction of the solar

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constant, increase of planetary albedo, or representing stratospheric aerosols by a single

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reflecting layer (e.g., Broccoli et al., 2003; Soden et al., 2002).

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The existing aerosol observations were used to build the global aerosol datasets with pre-

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calculated aerosol optical/microphysical characteristics that could be implemented in

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climate models (Stenchikov et al., 1998; Stenchikov, 2016; Ramachandran et al., 2000; Sato

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et al., 1993; Hansen et al., 2002; Schmidt et al., 2011; Tett et al., 2002; Ammann et al.,

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2003). One approach is to use the observed/reconstructed aerosol optical depth (usually in

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visible) and assume aerosol composition and size distribution to calculate aerosol extinction,

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single scattering albedo, and asymmetry parameter required for radiative transfer models as

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input (Stenchikov et al., 1998; Sato et al., 1993). Another approach uses the empirical

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estimates of SO2 emissions and a simplified model to distribute them globally and to obtain

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the aerosol optical parameters (Ammann et al., 2003; Gao et al., 2008). Ammann et al.

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(2003) and Sato et al. (1993) datasets have essentially provided the bases for

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implementing volcanic aerosols in virtually all of the climate models that have performed the

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20th-century climate integrations within IPCC AR4 (Stenchikov et al., 2006; Forster et al.,

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2007).

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For the IPCC AR5 and CMIP6, the improved “gap-filled” SAGE II Version 6 aerosol

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product from (Thomason and Peter, 2006) was employed (Arfeuille et al., 2013; Zanchettin

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et al., 2016). All three stratospheric optical depths (SATO, AMMAN, and CMIP6) in Figure

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9.1 vary by about 30%, with Amman’s optical depth being the largest and CMIP6 being the

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smallest.

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Figure 9.2 and 9.3 compare the all-sky shortwave (SW), longwave (LW), and SW+LW

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instantaneous radiative forcing at the top of the atmosphere and perturbations of heating rates

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calculated using SATO and CMIP6 inputs within the GFDL CM2.1 (Delworth et al., 2006)

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employing a double radiation call. To calculate optical characteristics of stratospheric

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aerosols for the SATO case, it was assumed that the aerosol has lognormal distribution with

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the time-and-latitude-varying effective radii and a fixed geometric width of 1.8 µm

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(SATO1.8) or 2.0 µm (SATO2). Despite the differences in the input information and

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assumptions, the changes in total radiative balance for the three datasets appear to be quite

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close. Both SATO’s datasets slightly overestimate the SW radiative forcing in comparison

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with (Minnis et al. 1993). The CMIP6 heating rates appear to be higher than expected

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(Stenchikov et al., 1998) and shifted toward theSW heating. Typical stratospheric sulfate

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from 2.5 µm where solar flux is weak. This is why LW heating is expected to prevail

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contributing about 70% of the effect (Stenchikov et al., 1998). The stratospheric heating is

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important, as it controls stratospheric dynamic responses (Ramaswamy et al., 2006).

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The complexity of radiative, microphysical, and transport processes forced by volcanic

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aerosols suggests that it is important to calculate aerosol radiative effects interactively with

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the aerosol plume development rather than use a pre-calculated set of aerosol optical

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parameters. To accomplish this, it is necessary to know the SO2 volcanic emissions (Krueger

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et al., 2000; Hopfner et al., 2013; 2015) and be able to calculate development, transport, and

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decay of a volcanic aerosol layer.

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The “bulk” aerosol models calculate SO2 to H2SO4 conversion and transport their bulk

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concentrations. Sulfate aerosols are assumed to form instantaneously with the prescribed size

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distribution (Timmreck et al., 1999; Oman et al., 2006a; and Aquila et al., 2012) that defines

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aerosol optical properties and deposition rates. Modal aerosol models keep track of

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aerosol number-density approximating the aerosol size distribution by a few log-normal

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modes with the prescribed width and varying modal radii, accounting for coagulation,

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condensation growth, and size-dependent gravitational settling (Niemeier et al., 2009; Bruhl

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et al., 2015; Dhomze et al., 2014; LeGrande et al., 2016; Sekiya et al., 2016). The aerosol

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sectional microphysical models are the most accurate but computationally more demanding

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(English et al., 2013; Mills et al., 2016).

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There are still significant discrepancies between models, and between the models and

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observations. This remains a challenging issue. The 1991 Pinatubo case-study is an important

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testbed where different approaches have been compared and could be further investigated.

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For example, in (Bruhl et al., 2015) the aerosol optical depth relaxes too fast, but in (Mills et

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al., 2016) the stratospheric aerosol plume decays too slowly and the initial SO2 loading has

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to be decreased by almost a factor of two to make the results consistent with observations.

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