Mineral dust is an important component of the climate system, affecting the radiation balance, cloud properties, biogeochemical cycles, regional circulation and precipitation, as well as having negative effects on aviation, solar energy generation and human health. Dust size and composition has an impact on all these processes. However, changes in dust size distribution and composition during transport, particularly for coarse particles, are poorly understood and poorly represented in climate models. Here we present new in situ airborne observations of dust in the Saharan Air Layer (SAL) and the marine boundary layer (MBL) at the beginning of its transatlantic transport pathway, from the AERosol Properties – Dust (AER-D) fieldwork in August 2015, within the peak season of North African dust export. This study focuses on coarse-mode dust properties, including size distribution, mass loading, shape, composition, refractive indices and optical properties. Size distributions from 0.1 to 100 µm diameter (d) are presented, fully incorporating the coarse and giant modes of dust. Within the MBL, mean effective diameter (d_eff) and volume median diameter (VMD) were 4.6 and 6.0 µm respectively, giant particles with a mode at 20–30 µm were observed, and composition was dominated by quartz and alumino-silicates at d > 1 µm. Within the SAL, particles larger than 20 µm diameter were always present up to 5 km altitude, in concentrations over 10⁻⁵ cm⁻³, constituting up to 40 % of total dust mass. Mean d_eff and VMD were 4.0 and 5.5 µm respectively. Larger particles were detected in the SAL than can be explained by sedimentation theory alone. Coarse-mode composition was dominated by quartz and alumino-silicates; the accumulation mode showed a strong contribution from sulfate-rich and sea salt particles. In the SAL, measured single scattering albedos (SSAs) at 550 nm representing d < 2.5 µm were 0.93 to 0.98 (mean 0.97). Optical properties calculated for the full size distribution (0.1 < d < 100 µm) resulted in lower SSAs of 0.91–0.98 (mean 0.95) and mass extinction coefficients of 0.27–0.35 m² g⁻¹ (mean 0.32 m² g⁻¹). Variability in SSA was mainly controlled by variability in dust composition (principally iron) rather than by variations in the size distribution, in contrast with previous observations over the Sahara where size is the dominant influence. It is important that models are able to capture the variability and evolution of both dust composition and size distribution with transport in order to accurately represent the impacts of dust on climate. These results provide a new SAL dust dataset, fully representing coarse and giant particles, to aid model validation and development.

This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F₀ using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F₀, around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors. The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for λ≥500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03. Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences. It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.

The Global Fire Assimilation System (GFAS) assimilates fire radiative power (FRP) observations from satellite-based sensors to produce daily estimates of biomass burning emissions. It has been extended to include information about injection heights derived from fire observations and meteorological information from the operational weather forecasts of ECMWF. Injection heights are provided by two distinct methods: the Integrated Monitoring and Modelling System for wildland fires (IS4FIRES) parameterisation and the one-dimensional plume rise model (PRM). A global database of daily biomass burning emissions and injection heights at 0.1° resolution has been produced for 2003–2015 and is continuously extended in near-real time with the operational GFAS service of the Copernicus Atmospheric Monitoring Service (CAMS). In this study, the two injection height data sets were compared with the new MPHP2 (MISR Plume Height Project 2) satellite-based plume height retrievals. The IS4FIRES parameterisation showed a better overall agreement than the observations, while the PRM was better at capturing the variability of injection heights. The performance of both parameterisations is also dependent on the type of vegetation. Furthermore, the use of biomass burning emission heights from GFAS in atmospheric composition forecasts was assessed in two case studies: the South AMerican Biomass Burning Analysis (SAMBBA) campaign which took place in September 2012 in Brazil, and a series of large fire events in the western USA in August 2013. For these case studies, forecasts of biomass burning aerosol species by the Composition Integrated Forecasting System (C-IFS) of CAMS were found to better reproduce the observed vertical distribution when using PRM injection heights from GFAS compared to aerosols emissions being prescribed at the surface. The globally available GFAS injection heights introduced and evaluated in this study provide a comprehensive data set for future fire and atmospheric composition modelling studies.

We present the results of the aerosol measurements carried out over the Aegean Sea during the Photochemical Activity and Solar Ultraviolet Radiation campaign held in Greece during June 1996. Simultaneous observations performed with a lidar and a double-monochromator spectrophotometer allowed us to retrieve the optical depth, the Ångström coefficient, and the backscatter-to-extinction ratio. The Sun photometric data can be used to improve quantitative aerosol measurements by lidar in the Planetary Boundary Layer. Systematic errors could arise otherwise, because the value of the backscatter-to-extinction ratio has to be supplied. Instead this ratio can be retrieved experimentally by use of an iterative solution of the lidar equation.

During the 2010 eruption of Eyjafjallajökull, improvements were made to the modeling procedure at the Met Office, UK, enabling peak ash concentrations within the volcanic cloud to be estimated. In this paper we describe the ash concentration forecasting method, its rationale and how it evolved over time in response to new information and user requirements. The change from solely forecasting regions of ash to also estimating peak ash concentrations required consideration of volcanic ash emission rates, the fraction of ash surviving near‐source fall‐out, and the relationship between predicted mean and local peak ash concentrations unresolved by the model. To validate the modeling procedure, predicted peak ash concentrations are compared against observations obtained by ground‐based and research aircraft instrumentation. This comparison between modeled and observed peak concentrations highlights the many sources of error and the uncertainties involved. Despite the challenges of predicting ash concentrations, the ash forecasting method employed here is found to give useful guidance on likely ash concentrations. Predicted peak ash concentrations lie within about one and a half orders of magnitude of the observed peak concentrations. A significant improvement in the agreement between modeled and observed values is seen if a buffer zone, accounting for positional errors in the predicted ash cloud, is used. Sensitivity of the predicted ash concentrations to the source properties (e.g., the plume height and the vertical distribution of ash at the source) is assessed and in some cases, seemingly minor uncertainties in the source specification have a large effect on predicted ash concentrations.