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Abstract Super‐coarse dust particles (diameters >10 μm) are evidenced to be more abundant in the atmosphere than model estimates and contribute significantly to the dust climate impacts. Since super‐coarse dust accounts for less dust extinction in the visible‐to‐near‐infrared (VIS‐NIR) than in the thermal infrared (TIR) spectral regime, they are suspected to be underestimated by remote sensing instruments operates only in VIS‐NIR, including Aerosol Robotic Networks (AERONET), a widely used data set for dust model validation. In this study, we perform a radiative closure assessment using the AERONET‐retrieved size distribution in comparison with the collocated Atmospheric Infrared Sounder (AIRS) TIR observations with comprehensive uncertainty analysis. The consistently warm bias in the comparisons suggests a potential underestimation of super‐coarse dust in the AERONET retrievals due to the limited VIS‐NIR sensitivity. An extra super‐coarse mode included in the AERONET‐retrieved size distribution helps improve the TIR closure without deteriorating the retrieval accuracy in the VIS‐NIR. 

Abstract. In this study, we developed a novel algorithm based on the collocatedModerate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR)observations and dust vertical profiles from the Cloud–Aerosol Lidar withOrthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosoloptical depth at 10 µm (DAOD10 µm) and the coarse-mode dusteffective diameter (Deff) over global oceans. The accuracy of theDeff retrieval is assessed by comparing the dust lognormal volumeparticle size distribution (PSD) corresponding to retrieved Deff withthe in situ-measured dust PSDs from the AERosol Properties – Dust(AER-D), Saharan Mineral Dust Experiment (SAMUM-2), and Saharan Aerosol Long-Range Transport and Aerosol–Cloud-InteractionExperiment (SALTRACE) fieldcampaigns through case studies. The new DAOD10 µm retrievals wereevaluated first through comparisons with the collocated DAOD10.6 µmretrieved from the combined Imaging Infrared Radiometer (IIR) and CALIOPobservations from our previous study (Zheng et al., 2022). The pixel-to-pixelcomparison of the two DAOD retrievals indicates a good agreement(R∼0.7) and a significant reduction in (∼50 %) retrieval uncertainties largely thanks to the better constraint ondust size. In a climatological comparison, the seasonal and regional(2∘×5∘) mean DAOD10 µm retrievals basedon our combined MODIS and CALIOP method are in good agreement with the twoindependent Infrared Atmospheric Sounding Interferometer (IASI) productsover three dust transport regions (i.e., North Atlantic (NA; R=0.9),Indian Ocean (IO; R=0.8) and North Pacific (NP; R=0.7)). Using the new retrievals from 2013 to 2017, we performed a climatologicalanalysis of coarse-mode dust Deff over global oceans. We found thatdust Deff over IO and NP is up to 20 % smaller than that over NA.Over NA in summer, we found a ∼50 % reduction in the numberof retrievals with Deff>5 µm from 15 to35∘ W and a stable trend of Deff average at 4.4 µm from35∘ W throughout the Caribbean Sea (90∘ W). Over NP inspring, only ∼5 % of retrieved pixels with Deff>5 µm are found from 150 to 180∘ E, whilethe mean Deff remains stable at 4.0 µm throughout eastern NP. To the best of our knowledge, this study is the first to retrieve both DAOD andcoarse-mode dust particle size over global oceans for multiple years. Thisretrieval dataset provides insightful information for evaluating dustlongwave radiative effects and coarse-mode dust particle size in models.