Global dust climatology based on MODIS C6.1 and OMI-OMAERUV satellite data for the period 2005 to 2019

Aerosol particles influence the Earth’s radiation budget, and thus weather and climate, through their interaction primarily with solar, but also with terrestrial radiation. Moreover, aerosol-cloud interactions are essential, since aerosols act as Cloud Condensation Nuclei (CCN) and/or Ice Nuclei (IN), and thus crucially affect cloud properties. Dust is a major aerosol type, accounting for a great fraction of the global aerosol mass, mostly originating from the global deserts). Dust aerosols exert a strong radiative forcing, while acting as CCN and/or IN, thus modifying the cloud physical optical and radiative properties as well as also cloud lifetime and precipitation. However, the direct and indirect effects of dust are strongly dependent on their spatial and temporal distribution, which still has a considerable degree of uncertainty. This uncertainty is due to limitations of our knowledge about the dust spatiotemporal variability, which is due to the strong variability both of the dust sources and emissions as well as their transport and removal processes. However, in the last two decades, significant steps have been made towards improving the ability to observe dust from satellites. Advanced retrieval algorithms enable to effectively derive key aerosol optical properties which are characteristic of their physical properties such as size and absorptivity. The availability of such aerosol data since the early 2000s offers nowadays the possibility to build satellite-based dust climatologies.

In the present study a global dust climatology is constructed using a satellite based algorithm. The algorithm is initialized with the latest editions of Collection 6.1 MODIS-Aqua and OMAER-UV OMI-Aura data spanning the 14-year period from 2005 to 2018. The raw data of the algorithm are: (1) spectrally resolved MODIS Aerosol Optical Depth-AOD and (2) OMI Aerosol Index-AI), both available on a daily basis and at 1°x1° latitude-longitude spatial resolution. The algorithm computes, using the spectral AOD values, the aerosol Angstrom Exponent (AE), which is finally used along with AI as the main algorithm input data that are characteristic of aerosol size (AE) and absorptivity (AI). By applying appropriate thresholds that ensure the coarse size and significant absorptivity of dust, the algorithm identifies presence of dust in the atmospheric column on a daily and 1°x1° basis over the entire globe and the period 2005-2018. The algorithm estimates the frequency of presence and the associated loading (in terms of dust optical depth, DOD) of dust on a monthly and annual basis. The 14-year study period enables the computation of climatological mean values, as well as the intra-annual and inter-annual variability and trends of dust. Specific emphasis is given to the world’s great deserts, as well as to regions undergoing important transport of dust.