[1] A size-segregated multicomponent aerosol algorithm, the Canadian Aerosol Module (CAM), was developed for use with climate and air quality models. It includes major aerosol processes in the atmosphere: generation, hygroscopic growth, coagulation, nucleation, condensation, dry deposition/sedimentation, below-cloud scavenging, aerosol activation, a cloud module with explicit microphysical processes to treat aerosol-cloud interactions and chemical transformation of sulphur species in clear air and in clouds. The numerical solution was optimized to efficiently solve the complicated size-segregated multicomponent aerosol system and make it feasible to be included in global and regional models. An internal mixture is assumed for all types of aerosols except for soil dust and black carbon which are assumed to be externally mixed close to sources. To test the algorithm, emissions to the atmosphere of anthropogenic and natural aerosols are simulated for two aerosol types: sea salt and sulphate. A comparison was made of two numerical solutions of the aerosol algorithm: process splitting and ordinary differential equation (ODE) solver. It was found that the process-splitting method used for this model is within 15% of the more accurate ODE solution for the total sulphate mass concentration and <1% accurate for sea-salt concentration. Furthermore, it is computationally more than 100 times faster. The sensitivity of the simulated size distributions to the number of size bins was also investigated. The diffusional behavior of each individual process was quantitatively characterized by the difference in the mode radius and standard deviation of a lognormal curve fit of distributions between the approximate solution and the 96-bin reference solution. Both the number and mass size distributions were adequately predicted by a sectional model of 12 bins in many situations in the atmosphere where the sink for condensable matter on existing aerosol surface area is high enough that nucleation of new particles is negligible. Total mass concentration was adequately simulated using lower size resolution of 8 bins. However, to properly resolve nucleation mode size distributions and minimize the numerical diffusion, a sectional model of 18 size bins or greater is needed. The number of size bins is more important in resolving the nucleation mode peaks than in reducing the diffusional behavior of aerosol processes. Application of CAM in a study of the global cycling of sea-salt mass accompanies this paper [Gong et al., 2002].
A method is introduced for inferring cloud optical depth from solar radiometric measurements made on an aircraft at altitude z. It is assessed using simulated radiometric measurements produced by a 3D Monte Carlo algorithm acting on fields of broken boundary layer clouds generated from Landsat imagery and a cloud-resolving model. The method uses upwelling flux and downwelling zenith radiance measured at two solar wavelengths where atmospheric optical properties above z are very similar but optical properties of the surface-atmosphere system below z differ. This enables estimation of cloud reflectance into nadir for upwelling diffuse flux and, finally, above z. An approximate one-dimensional radiative Green's function is used to roughly account for horizontal transport of photons in all, even broken, clouds. This method is compared to its surface-based counterpart and shown to be superior. Most notably, the aircraft-based approach deals easily with inhomogeneous land surfaces, is less susceptible to poor sampling, and need not account for aerosol below z.The algorithm appears as though it will have little difficulty inferring high-resolution time series of Շ 40 for most (single layer) clouds. For larger values of , biases emerge; particularly, underestimation for the statistically infrequent interiors of cumuliform clouds as photon leakage through cloud sides is not addressed. For the cumuliform and stratiform clouds used here, mean bias errors for retrieved are ϳ1 (or ϳ15%) and ϳ0.3 (or ϳ3%), respectively. For stratiform clouds with textured bases, performance is likely to improve slightly for flights just up from mean cloud base.
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