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[1] The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the parameterizations. Finally, SCMs are run for a 24-48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24-48 hr runs suggest that most models have problems in simulating boundary layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.

[1] The El Niño event of 1997-1998 caused a severe reduction of rainfall in Indonesia that promoted the spread of forest fires, leading to a pervasive haze in the region. Here we use fire coverage data from the 1997 World Fire Atlas with a review of other available data and literature to estimate the distribution of particulate emissions from August to November 1997 and the particle size and radiative properties. Our preferred estimate of the total particulate emissions is approximately 41 Tg. The emissions have been used to drive an atmospheric model to simulate the distribution of the haze and its direct radiative effect, with and without allowing for the effects of the smoke on the atmospheric evolution. Model diagnostics of the aerosol and its radiative impact are compared with measurements and output from other models. Large decreases in the incident solar flux at the surface are obtained in the region. The simulated global mean shortwave radiative forcing at the top of the atmosphere, averaged over the 4 months, is À0.32 Wm À2 . The accuracy of this calculation is discussed, and the importance of the Indonesian fires in particular and of biomass burning in general is assessed.