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DOI	10.5194/acp-22-3553-2022
	Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003-2017)
	Gkikas, Antonis; Proestakis, Emmanouil; Amiridis, Vassilis; Kazadzis, Stelios; Di Tomaso, Enza; Marinou, Eleni; Hatzianastassiou, Nikos; Kok, Jasper F.; Perez Garcia-Pando, Carlos
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	3553
结束页码	3578
卷号	22 期号:5 页码:26
英文摘要	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 (0.1 degrees x 0.1 degrees), 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 (R-2 = 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 (similar to 1.2) are recorded in the Bodele 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.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000772228200001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273893
作者单位	National Observatory of Athens; National Observatory of Athens; Universitat Politecnica de Catalunya; Barcelona Supercomputer Center (BSC-CNS); Helmholtz Association; German Aerospace Centre (DLR); University of Ioannina; University of California System; University of California Los Angeles; ICREA
推荐引用方式 GB/T 7714	Gkikas, Antonis,Proestakis, Emmanouil,Amiridis, Vassilis,et al. Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003-2017)[J],2022,22(5):26.
APA	Gkikas, Antonis.,Proestakis, Emmanouil.,Amiridis, Vassilis.,Kazadzis, Stelios.,Di Tomaso, Enza.,...&Perez Garcia-Pando, Carlos.(2022).Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003-2017).ATMOSPHERIC CHEMISTRY AND PHYSICS,22(5),26.
MLA	Gkikas, Antonis,et al."Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003-2017)".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.5(2022):26.