ArticleScientific reports2025
Aerosol optical depth trends and variability over the Middle East from MODIS, MISR, OMI, and AERONET observations.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study compares the performance of the aerosol optical depth (AOD) retrievals from four satellite sensors including MODIS-Terra, MODIS-Aqua, MISR, and OMI by evaluating them against the AERONET ground-based observations across the nine Middle Eastern sites from 2007 to 2021. The analysis reveals that while all the satellite products show reasonable correlation with the AERONET data, their accuracy varies depending on the sensor, location, and environmental conditions. The MODIS-Aqua product showed the highest correlation with AERONET data, with R value of approximately 0.8, while OMI showed the lowest correlation. High AOD values are observed over industrial zones, densely populated urban areas and dust-prone regions. The MODIS sensors, utilizing the combined Deep Blue and Dark Target algorithms, provide broad spatial coverage with consistent performance but tend to underestimate AOD under high aerosol loading. MISR, with its multi-angle viewing capability, demonstrates strong agreement with AERONET, particularly over bright surfaces. Seasonal patterns were evident, with all sensors detecting peak AOD values during summer months of about 0.55, driven by increased dust activity. Retrieval errors increased with AOD magnitude, i.e., RMSE rose by approximately 40% when AOD exceeded 0.5. The study reveals that higher aerosol concentrations are associated with increased retrieval errors, underscoring the need for region-specific calibration and algorithm refinement. These findings highlight the importance of the integrating multi-sensor data and updated retrieval algorithms to improve AOD estimation accuracy in arid and semi-arid regions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.