Preprints
https://doi.org/10.5194/amt-2023-259
https://doi.org/10.5194/amt-2023-259
24 Jan 2024
 | 24 Jan 2024
Status: this preprint is currently under review for the journal AMT.

Increasing Aerosol Optical Depth Spatial And Temporal Availability By Merging Datasets from Geostationary And Sun-Synchronous Satellites

Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan

Abstract. This comprehensive study analyzed aerosol observations from six Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) sensors. LEO sensors like MODIS and VIIRS, providing 1–2 daily global measurements, were contrasted with GEO sensors (AHI, ABIs), offering high-frequency data (~10 minutes) over specific regions. The Dark Target aerosol retrieval algorithm was applied to six sensors (3 LEO and 3 GEO), and their Level 2 aerosol optical depth (AOD) data were grided and merged into a quarter-degree latitude-longitude grid with a 30-minute temporal resolution. Validation of AOD at 550 nm against AERONET measurements across global locations showcased the merged product's robustness, revealing a global mean bias of approximately ±0.05, and 65.5 % of retrievals fell within an expected uncertainty range with a correlation coefficient of 0.83, underlining the reliability of the dataset. The new grided level 3 dataset significantly improved daily global coverage to nearly 45 %, overcoming the limitations of individual sensors, which typically range from 12 % to 25 %. Furthermore, the study emphasized the unprecedented ability of the merged dataset to approximate the diurnal cycle of AERONET AODs, offering insights into unexpected diurnal signatures. The resulting dataset's high spatiotemporal resolution and improved global coverage, especially in regions covered by GEO sensors (Americas and Asia), make it a valuable tool for diverse applications. Tracking aerosol transport from phenomena like wildfires and dust storms gains precision, enabling enhanced air quality forecasting and hindcasting. Additionally, the study positions the merged dataset as a significant asset for evaluating and inter-comparing regional or global model simulations, previously unattainable in such a gridded format. The dataset and fusion framework layout in this study has the potential to include data from recently (future) launched other GEO (FCI, AMI) and LEO (PACE, VIIRS-JPSS) sensors.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-259', Anonymous Referee #1, 29 Feb 2024
    • AC2: 'Reply on RC1', Pawan Gupta, 31 May 2024
  • RC2: 'Comment on amt-2023-259', Anonymous Referee #2, 18 Apr 2024
    • AC1: 'Reply on RC2', Pawan Gupta, 31 May 2024
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan

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Short summary
In this study, for the first time, we combined aerosol data from six satellites using a unified algorithm. The global datasets are generated at a high spatial resolution of about 25 km with an interval of 30 minutes. The new datasets are compared against ground truth and verified. They will be useful for various applications such as air quality monitoring, climate research, pollution diurnal variability, long-range smoke and dust transport, and evaluation of regional and global models.