Comparative analysis of MODIS, MISR, and AERONET climatology over the Middle East and North Africa

Abstract

Comparative analysis of Multi-angle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) products is performed over seven AERONET stations located in the Middle East and North Africa for the period of 2000-2015. Sites are categorized into dust, biomass burning, and mixed aerosol conditions. MISR and MODIS AOD agree during high-dust seasons but MODIS tends to underestimate AOD during low-dust seasons. Over dust-dominated sites, MODIS/Terra AODs indicate a negative trend over time, while MODIS/Aqua, MISR, and AERONET depict a positive trend. A deviation between MODIS/Aqua and MODIS/Terra was observed regardless of the geographic location and data sampling. The performance of MODIS is similar over the entire region with ∼ 64 % of AOD within the τ = ±0.05 ± 0.15τ AERO confidence range. MISR AOD retrievals fall within 84 % of the same confidence range for all sites examined here. Both MISR and MODIS capture aerosol climatology; however few cases were observed where one of the two sensors better captures the climatology over a certain location or AOD range than the other sensor. AERONET Level 2.0 version 3, MODIS Collection 6.1, and MISR V23 data have been used in analyzing the results presented in this study.

Evaluation and Comparison of MODIS Collection 6.1 and Collection 6 Dark Target Aerosol Optical Depth over Mainland China Under Various Conditions Including Spatiotemporal Distribution, Haze Effects, and Underlying Surface

“…The statistical relation between RMB and aerosol loading (shown as red curves of decline trend) indicates that the overestimation was obvious with low aerosol loading. Referring to related studies, similar significant overestimation results with few successful retrievals and small proportion of retrievals falling within EE lines were also noted in Africa and other bare lands of the world (Farahat 2019;Wei, Li, et al, 2019). In contrast, the retrievals in Western China did not perform well, with R 2 being only 0.73 and the slope of the regression lines being 1.26, that is, much greater than 1.…”

ModIs Dust AeroSol (MIDAS): A global fine resolution dust optical depth dataset

“…Over N. Africa, as well as in other dust rich environments, the positive reanalysis-satellite biases are mainly linked with the overestimation of GOCART dust aerosol amounts, with respect to a variety of spaceborne observations, as it has been discussed by Yu et al (2010) and Chin et al (2014). Moreover, over bright surfaces MERRA-2 assimilates uncorrected MISR AODs, which are higher than the corresponding MODIS retrievals, particularly at low AOD conditions, as it has been shown by and Farahat (2019). From a global and longterm perspective, the positive and negative deviations of an enormous number of pairs span from -0.3 to 0.3 and are almost equally separated around zero resulting in a Gaussian frequency distribution ( Fig.…”

Air Quality Over Major Cities of Saudi Arabia During Hajj Periods of 2019 and 2020

“…The major parts of Saudi Arabia are occupied by desert, during the summer season with strong winds, desert soils uplifted in the atmosphere, cause heavy aerosols loading (Alam et al 2014 ; Farahat et al 2015 ; PME 2012 ). The desert areas of Saudi Arabia suffer from higher concentrations of particulate matter due to dust storms and construction activities (Alam et al 2014 ; Farahat et al 2016 ; Farahat 2019 ; Khodeir et al 2012 ), with higher Ozone concentration and photochemical smog depending on the meteorological conditions (Lelieveld et al 2009 ). Large number of vehicles on the road cause greenhouse gas emissions and volatile organic compounds (VOCs) (Rahman et al 2017 ).…”