One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide column-integrated aerosol measurements, but observationally constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high-resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean Sea and parts of central Asia and the Atlantic and Indian oceans between 2007 and 2016. The horizontal resolution is 0.1^∘ latitude × 0.1^∘ longitude in a rotated grid, and the temporal resolution is 3 h. The reanalysis was produced using local ensemble transform Kalman filter (LETKF) data assimilation in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper-air variables (dust mass concentrations and the extinction coefficient), surface variables (dust deposition and solar irradiance fields among them) and total column variables (e.g. dust optical depth and load). Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 µm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first guess, which proves the consistency of the data assimilation method. Independent evaluation using Aerosol Robotic Network (AERONET) dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias = −0.05, RMSE = 0.12 and r = 0.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g. poor representation of small-scale emission processes), the presence of aerosols other than dust in the observations used in the evaluation and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via Thematic Real-time Environmental Distributed Data Services (THREDDS) at BSC and is freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98 (last access: 10 June 2022).

In this paper, characterization of the optical and microphysical properties of extremely fresh biomass burning aerosol is presented. This work aims to characterize, for the first time to our knowledge, freshly formed smoke particles observed only a few minutes after they were emitted from a nearby forest fire. The smoke particles were detected by combining passive (sun-photometer) and active (Raman lidar) techniques. On 14 August 2021, an EARLINET (European Aerosol Research Lidar Network) multi-wavelength Raman lidar and a co-located AERONET sun-photometer in Potenza, South Italy, observed an extremely fresh smoke plume. The lidar measurements, carried out from 22:27 to 02:16 UTC, revealed a thick biomass burning layer below 2.7 km. The particle depolarization ratio at 532 nm was 0.025, and lidar ratios at 355 and 532 nm were, respectively, 40 and 38 sr. The mean value of the Ångström exponent was 1.5. The derived size distribution was bimodal with a peak at 0.13 µm, an effective radius mean value of 0.15 µm, and a single scattering albedo of 0.96 at all wavelengths. The real part of the refractive index was 1.58 and the imaginary was 0.006. The AERONET measurements at 5:34 UTC confirmed the lidar measurements.

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Between 14 March and 21 April 2022, an extensive investigation of an extraordinary Saharan dust intrusion over Europe was performed based on lidar measurements obtained by the European Aerosol Research Lidar Network (EARLINET). The dust episode was divided into two distinct periods, one in March and one in April, characterized by different dust transport paths. The dust aerosol layers were studied over 18 EARLINET stations, examining aerosol characteristics during March and April in four different regions (M-I, M-II, M-III, and M-IV and A-I, A-II, A-III, and A-IV, respectively), focusing on parameters such as aerosol layer thickness, center of mass (CoM), lidar ratio (LR), particle linear depolarization ratio (PLDR), and Ångström exponents (ÅE). In March, regions exhibited varying dust geometrical and optical properties, with mean CoM values ranging from approximately 3.5 to 4.8 km, and mean LR values typically between 36 and 54 sr. PLDR values indicated the presence of both pure and mixed dust aerosols, with values ranging from 0.20 to 0.32 at 355 nm and 0.24 to 0.31 at 532 nm. ÅE values suggested a range of particle sizes, with some regions showing a predominance of coarse particles. Aerosol Optical Depth (AOD) simulations from the NAAPS model indicated significant dust activity across Europe, with AOD values reaching up to 1.60. In April, dust aerosol layers were observed between 3.2 to 5.2 km. Mean LR values typically ranged from 35 to 51 sr at both 355 nm and 532 nm, while PLDR values confirmed the presence of dust aerosols, with mean values between 0.22 and 0.31 at 355 nm and 0.25 to 0.31 at 532 nm. The ÅE values suggested a mixture of particle sizes. The AOD values in April were generally lower, not exceeding 0.8, indicating a less intense dust presence compared to March. The findings highlight spatial and temporal variations in aerosol characteristics across the regions, during the distinctive periods. From 15 to 16 March 2022, Saharan dust significantly reduced UV-B radiation by approximately 14% over the ATZ station (Athens, GR). Backward air mass trajectories showed that the dust originated from the Western and Central Sahara when, during this specific case, the air mass trajectories passed over GRA (Granada, ES) and PAY (Payerne, CH) before reaching ATZ, maintaining high relative humidity and almost stable aerosol properties throughout its transport. Lidar data revealed elevated aerosol backscatter (b_aer) and PLDR values, combined with low LR and ÅE values, indicative of pure dust aerosols.