Aerosol indirect effects – general circulation model intercomparison and evaluation with satellite data

Abstract

Published by Copernicus Publications on behalf of the European Geosciences Union. 8698 J. Quaas et al.: Aerosol indirect effects -general circulation model intercomparisonbetween τ a and f cld . The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τ a , and parameterisation assumptions such as a lower bound on N d . Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5 Wm −2 . In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic τ a and satellite-retrieved N d -τ a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2 Wm −2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5 Wm −2 , with a total estimate of −1.2±0.4 Wm −2 .

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

“…This process, described as the "second AIE", may further influence the cloud fraction (CF) (Albrecht, 1989;Feingold et al, 2001). The interaction mechanisms between aerosols and clouds remain among the most uncertain processes in the global climate system in spite of a large number of studies made using both observations Koren et al, 2005;Krüger et al, 2004) and models (Suzuki et al, 2004;Quaas et al, 2009;Sena et al, 2016).…”

The importance of temporal collocation for the evaluation of aerosol models with observations

“…A lot of effort has gone into evaluating global aerosol models against observations Schulz et al, 2006;Textor et al, 2006Textor et al, , 2007Huneeus et al, 2011;Quaas et al, 2009;Koffi et al, 2012) in the framework of the AEROCOM (AEROsol Comparisons between Observations and Models) community (http://aerocom.met.no). Although this has allowed the community to identify weaknesses in models (and has driven further model development), less effort has gone into developing best practices when performing such an evaluation.…”

Implementation of aerosol–cloud interactions in the regional atmosphere–aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

“…Satellite retrievals have been used to evaluate the performance of the numerous GCMs and NWP models (e.g., Quaas et al, 2004Quaas et al, , 2009Zhang et al, 2005;Brunke et al, 2010;Cherian et al, 2012;Nam et al, 2014 Chepfer et al, 2010), and the CloudSat cloud radar (Marchand et al, 2009). To produce similar output to satellite data, COSP requires the grid mean vertical profile of temperature, humidity, hydrometer mixing ratios, cloud optical thickness and emissivity, the surface temperature, and emissivity from the model.…”

“…Estimates of effective radiative forcing and assessments of the radiative effects due to aerosol-cloud interactions to a large extent rely on numerical modeling. A large effort has been made to represent such effects in general circulation models (GCMs) (Penner et al, 2006;Quaas et al, 2009;Ghan et al, 2016). However, GCMs do not resolve the processes relevant for cloud dynamics well.…”