The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)

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