Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF
By Minghuai Wang, Steven Ghan, M. Ovchinnikov, Xiaohong Liu, R. Easter, E. Kassianov, Y. Qian, Hugh Morrison. 2011
157 citations recorded by the source corpus.
Abstract. Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multi-scale 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 physically-based 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 extent, by a smaller relative increase in CCN concentrations from PI to PD in the MMF (about 26 % smaller than that in CAM5). The smaller relative increase in CCN concentrations in the MMF is caused in part by a smaller increase in aerosol lifetime from PI to PD in the MMF, a positive feedback in aerosol indirect effects induced by cloud lifetime effects from aerosols. The smaller response in LWP to anthropogenic aerosols in the MMF model is consistent with observations and with high resolution model studies, which may indicate that aerosol indirect effects simulated in conventional global climate models are overestimated and point to the need to use global high resolution models, such as MMF models or global CRMs, to study aerosol indirect effects. The simulated total anthropogenic aerosol effect in the MMF is −1.05 W m−2, which is close to the Murphy et al. (2009) inverse estimate of −1.1±0.4 W m−2 (1σ) based on the examination of the Earth's energy balance. Further improvements in the representation of ice nucleation and low clouds in MMF are needed to refine the aerosol indirect effect estimate.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/058cc5008ec293f36d0cee167a5a307683e3929c
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Citations in the corpus
- A numerical study of the effect of different aerosol types on East Asian summer clouds and precipitation (2013, unknown): “, Menon and Rotstayn, 2006; Lohmann, 2008) and within the Multiscale Modeling Framework (MMF) (Wang et al., 2011), it is still not clear whether the aerosol invigoration effects on convective clouds can be captured by the conventional cloud parameterizations in GCMs or the MMF approach.”
- A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges (2015, background): “…two-moment microphysics schemes have large potentials to improve the simulation of interactions between aerosols and clouds [Rosenfeld et al., 2014; Wang et al., 2011], but a better understanding of the underlying processes and their interaction with the resolved cumulus dynamics in CPMs is needed.”
- Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges (2016, methodology): “The results from themultiscale modeling framework (MMF) in which cumulus parameterization is not needed (M. Wang et al. 2011) showed that simulated change in shortwave cloud forcing from anthropogenic aerosols is 20.77Wm22, which is less than half of that (21.79Wm22) calculated by the host CAM5…”
- Constraining cloud lifetime effects of aerosols using A‐Train satellite observations (2012, methodology): “[10] The larger Spop in CAM5 than in MMF is consistent with the previously documented stronger LWP response to CCN perturbation in CAM5 [Wang et al., 2011a].”