An example of aerosol pattern variability over bright surface using high resolution MODIS MAIAC: The eastern and western areas of the Dead Sea and environs

Abstract

The extreme rate of evaporation of the Dead Sea (DS) has serious implicatios for the surrounding area, including atmospheric conditions. This study analyzes the aerosol properties over the western and eastern parts of the DS during the year 2013, using MAIAC (Multi-Angle Implementation of Atmospheric Correction) for MODIS, which retrieves aerosol optical depth (AOD) data at a resolution of 1km. The main goal of the study is to evaluate MAIAC over the study area and determine, for the first time, the prevailing aerosol spatial patterns. First, the MAIAC-derived AOD data was compared with data from three nearby AERONET sites (Nes Ziona - an urban site, and Sede Boker and Masada - two arid sites), and with the conventional Dark Target (DT) and Deep Blue (DB) retrievals for the same days and locations, on a monthly basis throughout 2013. For the urban site, the correlation coefficient (r) for DT/DB products showed better performance than MAIAC (r=0.80, 0.75, and 0.64 respectively) year-round. However, in the arid zones, MAIAC showed better correspondence to AERONET sites than the conventional retrievals (r=0.58-0.60 and 0.48-0.50 respectively). We investigated the difference in AOD levels, and its variability, between the Dead Sea coasts on a seasonal basis and calculated monthly/seasonal AOD averages for presenting AOD patterns over arid zones. Thus, we demonstrated that aerosol concentrations show a strong preference for the western coast, particularly during the summer season. This preference, is most likely a result of local anthropogenic emissions combined with the typical seasonal synoptic conditions, the Mediterranean Sea breeze, and the region complex topography. Our results also indicate that a large industrial zone showed higher AOD levels compared to an adjacent reference-site, i.e., 13% during the winter season.

Satellite-based view of the aerosol spatial and temporal variability in the Córdoba region (Argentina) using over ten years of high-resolution data

“…For example, Kloog et al (2015) found r pearson = 0.85 between MAIAC/Aqua and AERONET data for Israel; Emili et al (2011) reported a similar adjusted linear model coefficient (R 2 adj = 0.67) in Ispra (Italy). Similar results were also found using AERONET sites in the East Coast of the United States (Lyapustin et al, 2011) and above arid (bright) areas surrounding the Dead Sea (Sever et al, 2017). Slightly higher correlations coefficients (up to r > 0.9) were found by Martins et al (2018) comparing MAIAC-Terra to two AERONET sites in the Amazon in the period 2011-2015.…”

“…Recently, a high-resolution algorithm (Multi-Angle Implementation of Atmospheric Correction, MAIAC) providing AOD at 1km-resolution was developed (Lyapustin et al, 2011 and, thus representing a promising tool to investigate atmospheric particles variability at the city scale (Chudnovsky et al 2013a). It has been already usefully employed investigating different areas of the world such as the United States (Chudnovsky et al, 2014;Lee H. et al, 2011;Lee M. et al, 2016), the Amazon region (Martins et al, 2018), Europe (Arvani et al, 2016;Emili et al, 2011;Stafoggia et al, 2017), the Middle East and Asia (Kloog et al, 2015;Sever et al, 2017;Xiao et al, 2017).…”

Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia

“…Nowadays, many satellites provide reliable AOD (aerosol optical depth) products that can be used through various techniques for PM estimations from space, such as the Advanced Very High Resolution Radiometer (AVHRR) [20,21], Multiangle Imaging Spectroradiometer (MISR) [22], Medium Resolution Imaging Spectrometer (MERIS) [23], Spinning Enhanced Visible and Infrared Imager (SEVIRI) [24] and Moderate Resolution Imaging Spectroradiometer (MODIS) [25][26][27][28]. Among the satellite data products, AOD provided by MODIS sensor on board Terra and Aqua satellites has been widely used for many applications due to its high retrieval accuracy over land and near daily global coverage at 10 km and 3 km spatial resolution [26,27,29].…”

Aerosol optical depth (AOD): spatial and temporal variations and association with meteorological covariates in Taklimakan desert, China

“…Currently, remote sensing (RS) technology is an important means to detect and monitor aerosol based on the AOD ( Badarinath et al, 2011 ; Ge et al, 2011 ; Ginoux et al, 2001 ; Huang et al, 2007 , 2009 ; Masoumi et al, 2013 ; Perry, Cliff & Jimenez-Cruz, 2004 ; Sever et al, 2017 ; Tegen & Fung, 1994 ; Wang et al, 2010 ). As a column-integrated quantity, AOD reflects aerosol column loading and the impact of aerosols on Earth’s radiation budgets ( Park, Ahn & Chang, 2007 ).…”