Examination of the aerosol indirect effect under contrasting environments during the ACE-2 experiment

Guo, Huan; Penner, Joyce E.; Herzog, Michael; Pawłowska, Hanna

doi:10.5194/acp-7-535-2007

Cited by 20 publications

(22 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, ship track studies show that anthropogenic aerosols can lead to less liquid water (Platnick et al, 2000;Coakley and Walsh, 2002), and satellite studies show both decreases and increases in LWP with increasing aerosols (Kaufman et al, 2005;Matsui et al, 2006). CRM studies have suggested that LWP can either increase or decrease with increasing aerosols, depending on the meteorological conditions (Ackerman et al, 2004;Jiang et al, 2006;Guo et al, 2007;Xue et al, 2008;Small et al, 2009). The decreasing LWP with increasing aerosols can be attributed to enhanced entrainment of dry air or enhanced evaporation of the more numerous smaller cloud droplets in polluted clouds.…”

Section: Comparison With Cam5mentioning

confidence: 99%

Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

et al. 2011

View full text Add to dashboard Cite

Abstract. Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multiscale nature of the interactions between aerosols, clouds and dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we use a multi-scale aerosol-climate model that treats aerosols and clouds across multiple scales to study aerosol indirect effects. This multi-scale aerosol-climate model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each vertical column of a GCM grid. The extension allows a more physicallybased treatment of aerosol-cloud interactions in both stratiform and convective clouds on the global scale in a computationally feasible way. Simulated model fields, including liquid water path (LWP), ice water path, cloud fraction, shortwave and longwave cloud forcing, precipitation, water vapor, and cloud droplet number concentration are in reasonable agreement with observations. The new model performs quantitatively similar to the previous version of the MMF model in terms of simulated cloud fraction and precipitation. The simulated change in shortwave cloud forcing from anthropogenic aerosols is −0.77 W m −2 , which is less than half of that (−1.79 W m −2 ) calculated by the host GCM (NCAR CAM5) with traditional cloud parameterizations and is also at the low end of the estimates of other conventional global aerosol-climate models. The smaller forcing in the MMF model is attributed to a smaller (3.9 %) increase in LWP from preindustrial conditions (PI) to present day (PD) compared with 15.6 % increase in LWP in stratiform clouds in CAM5. The difference is caused by a much smaller response in LWP to a given perturbation in cloud condensation nuclei (CCN) concentrations from PI to PD in the MMF (about one-third of that in CAM5), and, to a lesser

show abstract

Section: Comparison With Cam5mentioning

confidence: 99%

Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

et al. 2011

View full text Add to dashboard Cite

show abstract

“…Note that CF here is defined as the fraction of cloudy columns, and a cloudy column is a column containing one or more cloudy cells with liquid water mixing ratio >0.01 g/kg. The AIE (shortwave plus longwave) at the top-of-the-atmosphere is estimated by swapping the aerosol and meteorological conditions between the "CLEAN" and "POLL" cases and then calculating the radiative flux difference between the clean and polluted aerosol conditions under the same meteorological background (Guo et al, 2007b).…”

Section: Sensitivity To the Relative Dispersion (ε)mentioning

confidence: 99%

“…Consequently, the "CLEAN" clouds transform quickly from one stage (with efficient drizzle production) to another stage (between drizzling and non-drizzling). But for the "POLL" case, due to their continental origin and the strong large-scale subsidence (Guo et al, 2007b), these "POLL" clouds tend to precipitate less efficiently. Moreover, as shown in Fig.…”

Section: Sensitivity To the Relative Dispersion (ε)mentioning

confidence: 99%

“…Deeper analysis reveals that the smaller CF and LWP are due to the stabilization of the boundary layer by precipitation formation. Smaller precipitation with increasing r c results in higher entrainment drying and thereby a more efficient depletion of cloud water (Ackerman et al, 2004;Bretherton et al, 2007;Guo et al, 2007b). In the afternoon, the instantaneous CF and LWP (with r c =20 µm) are reduced as much as 60% and 50%, respectively.…”

Section: Sensitivity To the Critical Radius (R C )mentioning

confidence: 99%

See 1 more Smart Citation

Does the threshold representation associated with the autoconversion process matter?

2008

Self Cite

View full text Add to dashboard Cite

Abstract. Different ad hoc threshold functions associated with the autoconversion process have been arbitrarily used in atmospheric models. However, it is unclear how these ad hoc functions impact model results. Here systematic investigations of the sensitivities of climatically-important properties: CF (cloud fraction), LWP (liquid water path), and AIE (aerosol indirect effect) to threshold functions have been performed using a 3-D cloud-resolving model. It is found that the effect of threshold representations is larger on instantaneous values than on daily averages; and the effect depends on the percentage of clouds in their transitional stages of converting cloud water to rain water. For both the instantaneous values and daily averages, the sensitivity to the specification of critical radius is more significant than the sensitivity to the "smoothness" of the threshold representation (as embodied in the relative dispersion of droplet size distribution) for drizzling clouds. Moreover, the impact of threshold representations on the AIE is stronger than that on CF and LWP.

show abstract

“…The results regarding the hypothesized increase in cloud albedo or cloud optical thickness (COT) due to smaller and more numerous droplets, are however not as consistent. Some studies (Sporre et al, 2012;Chameides et al, 2002;Guo et al, 2007) have indeed found that the COT increases in polluted air masses while other studies find no correlation between COT and higher particle concentrations (Twohy et al, 2005;Costantino and Breon, 2013). The reasons for the diverging results are thought to be enhanced entrainment of dry air into the clouds due increased cloud droplet number concentrations (Ackerman et al, 2004;Wood, 2007;Bretherton et al, 2007) or/and that air masses with higher aerosol loading often are associated with drier meteorological conditions (Brenguier et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Aerosol indirect effects on continental low-level clouds over Sweden and Finland

et al. 2014

View full text Add to dashboard Cite

Abstract. Aerosol effects on low-level clouds over the Nordic Countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds is investigated using reanalysis data from the European Centre for Medium-Range Weather Forecasts.The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosolcloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.

show abstract

Examination of the aerosol indirect effect under contrasting environments during the ACE-2 experiment

Cited by 20 publications

References 61 publications

Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

Does the threshold representation associated with the autoconversion process matter?

Aerosol indirect effects on continental low-level clouds over Sweden and Finland

Contact Info

Product

Resources

About