Interpreting the cloud cover – aerosol optical depth relationship found in satellite data using a general circulation model

By Johannes Quaas, Bjorn Stevens, P. Stier, Ulrike Lohmann. 2009

192 citations recorded by the source corpus.

Abstract. Statistical analysis of satellite data shows a positive correlation between aerosol optical depth (AOD) and total cloud cover (TCC). Reasons for this relationship have been disputed in recent literature. The aim of this study is to explore how different processes contribute to one model's analog of the positive correlation between aerosol optical depth and total cloud cover seen in the satellite retrievals. We compare the slope of the linear regression between the logarithm of TCC and the logarithm of AOD, or the strength of the relationship, as derived from three satellite data sets to the ones simulated by a global aerosol-climate model. We analyse model results from two different simulations with and without a parameterisation of aerosol indirect effects, and using dry compared to humidified AOD. Perhaps not surprisingly we find that no single one of the hypotheses discussed in the literature is able to uniquely explain the positive relationship. However the dominant contribution to the model's AOD-TCC relationship can be attributed to aerosol swelling in regions where humidity is high and clouds are coincidentally found. This finding leads us to hypothesise that much of the AOD-TCC relationship seen in the satellite data is also carried by such a process, rather than the direct effects of the aerosols on the cloud fields themselves.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/043bb41aed0a70e1a3453b95acff743b0e3369db

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Citations in the corpus

Satellite-based estimate of global aerosol-cloud radiative forcing by marine warm clouds (2014, background): “These include: -0.8±0.5 Wm-2 under all-sky condition over ocean (Bellouin et al., 2013); -0.93±0.44 and -0.82±0.52 Wm-2 for ocean cloudy-sky condition from model and scaled model estimates, respectively (Quaas et al., 2009); - 0.2±0.1 Wm-2 over ocean (satellite-based estimation; Quaas et al., 2008).”
Bounding Global Aerosol Radiative Forcing of Climate Change (2020, background): “…arate the role of aerosols from the impact of retrieval biases (Brennan et al., 2005; Várnai1179 & Marshak, 2009) and meteorological covariations (Quaas et al., 2010; Chand et al., 2012;1180 Grandey et al., 2013).1181 GCMs typically show an increase in C and a corresponding negative rapid…”
Constraining the aerosol influence on cloud fraction (2016, methodology): “Studies using general circulation models indicate that aerosol hygroscopic growth is responsible for a large part of the positive AOD-CF relationship [Quaas et al., 2010; Grandey et al., 2013]; cloud resolving models indicate that aerosols may have a very small [Stevens and Seifert, 2008] or even sl”
Constraining the aerosol influence on cloud liquid water path (2018, background): “The key difficulty in interpreting observed aerosol–cloud relationships is separating the causal impact of aerosols (the change in LWP caused by an aerosol perturbation) from the confounding role of local meteorology (e.g. Quaas et al., 2010) and retrieval errors (e.g. Várnai and Marshak, 2009).”