Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003–2017)

Quantifying the dust optical depth (DOD) and its uncertainty across spatiotemporal scales is key to understanding and constraining the dust cycle and its interactions with the Earth System. This study quantifies the DOD along with its monthly and year-to-year variability between 2003 and 2017 at global and regional levels based on the MIDAS (ModIs Dust AeroSol) dataset, which combines Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua retrievals and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis products. We also describe the annual and seasonal geographical distributions of DOD across the main dust source regions and transport pathways. MIDAS provides columnar mid-visible (550 nm) DOD at fine spatial resolution (), expanding the current observational capabilities for monitoring the highly variable spatiotemporal features of the dust burden. We obtain a global DOD of 0.032±0.003 – approximately a quarter (23.4 %±2.4 %) of the global aerosol optical depth (AOD) – with about 1 order of magnitude more DOD in the Northern Hemisphere (0.056±0.004; 31.8 %±2.7 %) than in the Southern Hemisphere (0.008±0.001; 8.2 %±1.1 %) and about 3.5 times more DOD over land (0.070±0.005) than over ocean (0.019±0.002). The Northern Hemisphere monthly DOD is highly correlated with the corresponding monthly AOD (R2=0.94) and contributes 20 % to 48 % of it, both indicating a dominant dust contribution. In contrast, the contribution of dust to the monthly AOD does not exceed 17 % in the Southern Hemisphere, although the uncertainty in this region is larger. Among the major dust sources of the planet, the maximum DODs (∼1.2) are recorded in the Bodélé Depression of the northern Lake Chad Basin, whereas moderate-to-high intensities are encountered in the Western Sahara (boreal summer), along the eastern parts of the Middle East (boreal summer) and in the Taklamakan Desert (spring). Over oceans, major long-range dust transport is observed primarily along the tropical Atlantic (intensified during boreal summer) and secondarily in the North Pacific (intensified during boreal spring). Our calculated global and regional averages and associated uncertainties are consistent with some but not all recent observation-based studies. Our work provides a simple yet flexible method to estimate consistent uncertainties across spatiotemporal scales, which will enhance the use of the MIDAS dataset in a variety of future studies. Antonis Gkikas acknowledges support by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the 2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers (ATLANTAS, project number 544), as well as support from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions (grant no. 749461; DUST-GLASS). Vassilis Amiridis acknowledges support from the European Research Council (grant no. 725698; D-TECT). Eleni Marinou was funded by a DLR VO-R young investigator group and the Deutscher Akademischer Austauschdienst (grant no. 57370121). Jasper F. Kok acknowledges support from National Science Foundation (NSF) grant 1552519. Carlos Pérez García-Pando acknowledges support from the European Research Council (grant no. 773051; FRAGMENT); the AXA Research Fund; and the Spanish Ministry of Science, Innovation and Universities (grant nos. RYC-2015-18690 and CGL2017-88911-R). The authors acknowledge support from the DustClim project as part of ERA4CS, an ERA-NET project initiated by JPI Climate and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR), with cofunding by the European Union (grant no. 690462). PRACE (Partnership for Advanced Computing in Europe) and RES (Red Española de Supercomputación) are acknowledged for awarding access to the MareNostrum Supercomputer in the Barcelona Supercomputing Center. We acknowledge support of this work by the PANhellenic infrastructure for Atmospheric Composition and climatE chAnge (PANACEA) project (grant no. MIS 5021516), which is implemented under the Horizon 2020 Action of Reinforcement of the Research and Innovation Infrastructure, funded by the Operational Programme Competitiveness, Entrepreneurship, and Innovation (NSRF 2014–2020) and cofinanced by Greece and the European Union (under the European Regional Development Fund). NOA members acknowledge support from the Stavros Niarchos Foundation (SNF). The authors acknowledge support by the COST Action InDust (grant no. CA16202), supported by COST (European Cooperation in Science and Technology). The authors would like to thank Andrew Mark Sayer for his valuable and constructive comments. The authors would like also to thank Thanasis Georgiou for developing the ftp server on which the MIDAS dataset is stored.