Aerosol Types Identification over the Arabian Peninsula Using AERONET Products: Evaluation with Multisource Datasets

Knowing aerosol size and composition is essential for studying aerosol radiative forcing (ARF) and human health impacts, identifying their sources, and improving satellite aerosol estimation methods. An aerosol classification technique (T1) is proposed here using K-mean clustering analysis based on Aerosol Optical Depth (AOD500 nm) vs Angstrom Exponent (AE440–870 nm) data (1999–2018) from Aerosol Robotic Network (AERONET) in the Arabian Peninsula. The proposed classified aerosol types are: (1) Clean background/clean maritime (CB/CM): AOD < 0.20 AE < 1.35; (2) Clean Continental (CC): AOD < 0.20 AE > 1.35; (3) Desert Dust (DD): AOD > 0.20 AE < 0.6; (4) Dusty Mixture (DM): AOD > 0.20 0.60 < AE < 1.0; (5) Urban Industrial (UI): AOD > 0.20 1.0 < AE < 1.35; and (6) Biomass Burning (BB): AOD > 0.20 AE > 1.35. Further verification of our results was conducted with respect to AERONET depolarization ratio (δ), surface observations (e.g., wind speed, relative humidity, and visibility), and dust RGB products from Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG) satellite. The T1 reveals that DD was prevalent at the Solar Village in Riyadh (51