Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Investigation of June 2020 Giant Saharan Dust Storm Using Remote Sensing Observations and Model Reanalysis

Version 1 : Received: 4 July 2021 / Approved: 5 July 2021 / Online: 5 July 2021 (13:16:28 CEST)

How to cite: Asutosh, A.; Vinoj, V.; Nuncio, M. Investigation of June 2020 Giant Saharan Dust Storm Using Remote Sensing Observations and Model Reanalysis. Preprints 2021, 2021070100. https://doi.org/10.20944/preprints202107.0100.v1 Asutosh, A.; Vinoj, V.; Nuncio, M. Investigation of June 2020 Giant Saharan Dust Storm Using Remote Sensing Observations and Model Reanalysis. Preprints 2021, 2021070100. https://doi.org/10.20944/preprints202107.0100.v1

Abstract

This paper investigates the characteristics and impact of a major Saharan dust storm during June 14th -19th 2020 to atmospheric radiative and thermodynamics properties over the Atlantic Ocean. The event witnessed the highest ever aerosol optical depth (close to 2 during the peak of the storm) for June since 2002. The satellites and high-resolution model reanalysis products well captured the origin, spread and the effects of the dust storm. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) profiles, lower angstrom exponent values (~ 0.12) and higher aerosol index value (> 4) tracked the presence of elevated dust. It was found that the dust AOD was as much as 250-300% higher than their climatology resulting in an atmospheric radiative forcing ~200% larger. As a result, elevated warming ( 8-16 %) was observed, followed by a drop in relative humidity(2-4%) in the atmospheric column, as evidenced by both in-situ and satellite measurements. Quantifications such as these for extreme dust events provide significant insights that may help in understanding their climate effects, including improvements to dust simulations using chemistry-climate models

Keywords

Dust storm; Aerosols; Satellite remote sensing; Radiative forcing; Thermodynamics

Subject

Environmental and Earth Sciences, Remote Sensing

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