On the Spatio-Temporal Characteristics of Aerosol Optical Depth in the Arabian Gulf Zone

Abstract

The article investigates some of the available measurements (Terra MODIS satellite data) of the aerosol optical depth (AOD) taken in the Arabian Gulf, a zone traditionally affected by intense sand-related (or even sand-driven) meteorological events. The Principal Component Analysis (PCA) reveals the main subspace of the data. Clustering of the series was performed after selecting the optimal number of groups using 30 different methods, such as the silhouette, gap, Duda, Dunn, Hartigan, Hubert, etc. The AOD regional and temporal tendency detection was completed utilizing an original algorithm based on the dominant cluster found at the previous stage, resulting in the regional time series (RTS) and temporal time series (TTS). It was shown that the spatially-indexed time series (SITS) agglomerates along with the first PC. In contrast, six PCs are responsible for 60.5% of the variance in the case of the temporally-indexed time series (TITS). Both RTS and TTS are stationary in trend and fit the studied data series set well.

Downscaling MERRA-2 Reanalysis PM2.5 Series over the Arabian Gulf by Inverse Distance Weighting, Bicubic Spline Smoothing, and Spatio-Temporal Kriging

“…The first incorporates the PM 2.5 originated from industrial sources and dust storms from the desert (particularly in spring and the beginning of autumn) [ 10 , 11 ]. The second reflects the influence of the dust transported over the Arabian Gulf from North Africa [ 77 , 78 , 79 , 80 ].…”

“…The first incorporates the PM 2.5 originated from industrial sources and dust storms from the desert (particularly in spring and the beginning of autumn) [10,11]. The second reflects the influence of the dust transported over the Arabian Gulf from North Africa [77][78][79][80]. This approach to optimizing the IDW model underscores a balance between methodological rigor in parameter selection and flexibility in model customization, ensuring robustness and adaptability in spatial data analysis.…”

Development and Testing a Method for Retrieving Atmospheric Aerosol Optical Thickness based on the Solar Intensity from the Sun-photometer Data

“…The parameters utilized in this estimation are derived from applying several corrections. Comparing the method in processing the sun-photometer data (Xun et al, 2021;Bărbulescu, 2022), the Langley plot and Lambert-Beer Law are useful to support several methods in retrieving the solar intensity from the extraterrestrial atmosphere. In several atmospheric corrections of optical remote sensing using satellite sensors, the AOT's values play an essential role in arranging a Look Up Table (LUT) for scattering parameters (Aminuddin et al, 2018a;Jin et al, 2021;Kuze, 2012b).…”

Statistical Analysis and Modeling of the CO2 Series Emitted by Thirty European Countries

“…Despite the necessity of emissions' reduction being understood [25][26][27][28][29][30], there exist differences among countries related to carbon emissions' responsibility [31,32]. So, most studies in the field discuss the responsibility for embodied CO 2 emissions in international trade [25,31].…”