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Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark‐Target Algorithm: 1. Dust Detection

Yaping Zhou, Robert C. Levy, Lorraine A. Remer and 3 more

Earth and Space Science · 2020

doi:10.1029/2020ea001221 (opens in a new tab)

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Abstract

Abstract To prepare for implementation of a new aerosol retrieval specifically designed for dust aerosol over ocean in the operational Dark‐Target (DT) algorithms for the Moderate‐resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors, we focus on the challenge of detecting dust. We first survey the literature on existing dust detection algorithms and then develop an innovative algorithm that combines near‐UV (deep blue), visible, and thermal infrared (TIR) wavelength spectral tests. The new detection algorithm is applied to Terra and Aqua MODIS granules and compared with other dust detection possibilities from existing MODIS products. Quantitative evaluation of the new dust detection algorithm is conducted using both a collocated AERONET‐MODIS data set and collocated Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)‐MODIS data set. From comparison with both AERONET and CALIOP measurements, we estimate the new dust detection algorithm detects about 30% of weakly dusty pixels and more than 80% of heavily dusty pixels, with false detections in the range of 1–2%. The very low false detection rate is particularly noteworthy in comparison with existing literature. Compared with the dust flag currently available as part of the MODIS cloud mask product (MOD35/MYD35), and dust classification based on commonly used thresholds with aerosol optical depth (AOD) and Angstrom exponent (AE), the new dust detection algorithm finds more dusty pixels and fewer false detections.

Abstract licence: CC BY-NC-ND

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