In this paper, we present the implementation and evaluation of the aerosol microphysics module SALSA2.0 in the framework of the aerosol–chemistry–climate model ECHAM-HAMMOZ. It is an alternative microphysics module to the default modal microphysics scheme M7 in ECHAM-HAMMOZ. The SALSA2.0 implementation within ECHAM-HAMMOZ is evaluated against observations of aerosol optical properties, aerosol mass, and size distributions, comparing also to the skill of the M7 implementation. The largest differences between the implementation of SALSA2.0 and M7 are in the methods used for calculating microphysical processes, i.e., nucleation, condensation, coagulation, and hydration. These differences in the microphysics are reflected in the results so that the largest differences between SALSA2.0 and M7 are evident over regions where the aerosol size distribution is heavily modified by the microphysical processing of aerosol particles. Such regions are, for example, highly polluted regions and regions strongly affected by biomass burning. In addition, in a simulation of the 1991 Mt. Pinatubo eruption in which a stratospheric sulfate plume was formed, the global burden and the effective radii of the stratospheric aerosol are very different in SALSA2.0 and M7. While SALSA2.0 was able to reproduce the observed time evolution of the global burden of sulfate and the effective radii of stratospheric aerosol, M7 strongly overestimates the removal of coarse stratospheric particles and thus underestimates the effective radius of stratospheric aerosol. As the mode widths of M7 have been optimized for the troposphere and were not designed to represent stratospheric aerosol, the ability of M7 to simulate the volcano plume was improved by modifying the mode widths, decreasing the standard deviations of the accumulation and coarse modes from 1.59 and 2.0, respectively, to 1.2 similar to what was observed after the Mt. Pinatubo eruption. Overall, SALSA2.0 shows promise in improving the aerosol description of ECHAM-HAMMOZ and can be further improved by implementing methods for aerosol processes that are more suitable for the sectional method, e.g., size-dependent emissions for aerosol species and size-resolved wet deposition.

Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.

We present the implementation and evaluation of a sectional aerosol microphysics module SALSA within the aerosol-climate model ECHAM5-HAM. This aerosol microphysics module has been designed to be flexible and computationally efficient so that it can be implemented in regional or global scale models. The computational efficiency has been achieved by minimising the number of variables needed to describe the size and composition distribution. The aerosol size distribution is described using 10 size classes with parallel sections which can have different chemical compositions. Thus in total, the module tracks 20 size sections which cover diameters ranging from 3 nm to 10 μm and are divided into three subranges, each with an optimised selection of processes and compounds. The implementation of SALSA into ECHAM5-HAM includes the main aerosol processes in the atmosphere: emissions, removal, radiative effects, liquid and gas phase sulphate chemistry, and the aerosol microphysics. The aerosol compounds treated in the module are sulphate, organic carbon, sea salt, black carbon, and mineral dust. In its default configuration, ECHAM5-HAM treats aerosol size distribution using the modal method. In this implementation, the aerosol processes were converted to be used in a sectional model framework. The ability of the module to describe the global aerosol properties was evaluated by comparing against (1) measured continental and marine size distributions, (2) observed variability of continental number concentrations, (3) measured sulphate, organic carbon, black carbon and sea-salt mass concentrations, (4) observations of aerosol optical depth (AOD) and other aerosol optical properties from satellites and AERONET network, (5) global aerosol budgets and concentrations from previous model studies, and (6) model results using M7, which is the default aerosol microphysics module in ECHAM5-HAM. The evaluation shows that the global aerosol properties can be reproduced reasonably well using a coarse resolution of 10 sections in size space. The simulated global aerosol budgets are within the range of previous studies. Surface concentrations of sulphate and carbonaceous species have an annual mean within a factor of two of the observations. The simulated sea-salt concentrations reproduce the observations within a factor of two, apart from the Southern Ocean over which the concentrations are within a factor of five. Regionally, AOD is in a relatively good agreement with the observations (within a factor of two). At mid-latitudes the observed AOD is captured well, while at high-latitudes as well as in some polluted and dust regions the modelled AOD is significantly lower than observed. Regarding most of the investigated aerosol properties, the SALSA and the modal aerosol module M7 perform comparably well against observations. However, SALSA reproduces the observed number concentrations and the size distribution of CCN sized particles much more accurately than M7, and is therefore a good choice for aerosol-cloud interaction studies in global models. Our study also shows that when activation type nucleation in the boundary layer is included, the observed concentration of particles under 50 nm in diameter are reproduced much better compared to when only binary nucleation in the free troposphere is assumed.

Atmospheric lidar measurements were carried out at Elandsfontein measurement station, on the eastern Highveld approximately 150 km east of Johannesburg in South Africa throughout 2010. The height of the planetary boundary layer (PBL) top was continuously measured using a Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended). High atmospheric variability together with a large surface temperature range and significant seasonal changes in precipitation were observed, which had an impact on the vertical mixing of particulate matter, and hence, on the PBL evolution. The results were compared to radiosondes, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) space-borne lidar measurements and three atmospheric models that followed different approaches to determine the PBL top height. These models included two weather forecast models operated by ECMWF (European Centre for Medium-range Weather Forecasts) and SAWS (South African Weather Service), and one mesoscale prognostic meteorological and air pollution regulatory model TAPM (The Air Pollution Model). The ground-based lidar used in this study was operational for 4935 h during 2010 (49% of the time). The PBL top height was detected 86% of the total measurement time (42% of the total time). Large seasonal and diurnal variations were observed between the different methods utilised. High variation was found when lidar measurements were compared to radiosonde measurements. This could be partially due to the distance between the lidar measurements and the radiosondes, which were 120 km apart. Comparison of lidar measurements to the models indicated that the ECMWF model agreed the best with mean relative difference of 15.4%, while the second best correlation was with the SAWS model with corresponding difference of 20.1%. TAPM was found to have a tendency to underestimate the PBL top height. The wind speeds in the SAWS and TAPM models were strongly underestimated which probably led to underestimation of the vertical wind and turbulence and thus underestimation of the PBL top height. Comparison between ground-based and satellite lidar shows good agreement with a correlation coefficient of 0.88. On average, the daily maximum PBL top height in October (spring) and June (winter) was 2260 m and 1480 m, respectively. To our knowledge, this study is the first long-term study of PBL top heights and PBL growth rates in South Africa.