Articles | Volume 24, issue 10
https://doi.org/10.5194/acp-24-6385-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-6385-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 May 2024
Research article |
| 31 May 2024
| 31 May 2024
Intercomparison of aerosol optical depths from four reanalyses and their multi-reanalysis consensus
Marine Meteorology Division, Naval Research Laboratory, Monterey, CA, USA
Jeffrey S. Reid
Marine Meteorology Division, Naval Research Laboratory, Monterey, CA, USA
Melanie Ades
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Angela Benedetti
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Peter R. Colarco
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Arlindo da Silva
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Tom F. Eck
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research II, University of Maryland, Baltimore County, Baltimore, MD, USA
Johannes Flemming
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Edward J. Hyer
Marine Meteorology Division, Naval Research Laboratory, Monterey, CA, USA
Zak Kipling
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Samuel Rémy
Atmospheric Composition Department, HYGEOS, Lille, France
Tsuyoshi Thomas Sekiyama
Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan
Taichu Tanaka
Information Infrastructure Department, Japan Meteorological Agency, Tokyo, Japan
Keiya Yumimoto
Research Institute for Applied Mechanics, Kyushu University, Kasuga, Japan
Jianglong Zhang
Department of Atmospheric Sciences, University of North Dakota, Grand Forks, ND, USA
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- Deciphering Long-Term Variation of Aerosol Characteristics and Their Climatic Implication over the World’s Wettest Place: Mawsynram M. Devi et al. https://doi.org/10.1007/s12524-025-02374-x
- Radiative effects of elevated aerosol layers on elevated inversions and weakening of boundary layer inversions M. Aloysius et al. https://doi.org/10.1016/j.jastp.2026.106860
- Global fields of daily accumulation-mode particle number concentrations using in situ observations, reanalysis data, and machine learning A. Ovaska et al. https://doi.org/10.5194/ar-3-589-2025
- Observation of Wildfire Smoke Particles That Accumulated Secondary Aerosol during Long-Range Transport J. Lee et al. https://doi.org/10.1021/acsearthspacechem.5c00172
- Aircraft engine dust ingestion at global airports C. Ryder et al. https://doi.org/10.5194/nhess-24-2263-2024
- Atmospheric aerosols in the South Pacific: A regional baseline and characterization of aerosol fractions A. Isaza et al. https://doi.org/10.1016/j.atmosenv.2025.121048
- Aerosol–Cloud Interactions over the Indian Subcontinent Using an Information-Theoretic Approach S. Budakoti et al. https://doi.org/10.34133/olar.0116
- The 2024 report of the Lancet Countdown on health and climate change: facing record-breaking threats from delayed action M. Romanello et al. https://doi.org/10.1016/S0140-6736(24)01822-1
- A novel framework for assessing regional wildfires contributions to biomass burning aerosol optical depth M. Broda et al. https://doi.org/10.5194/acp-25-14015-2025
- Relative contributions of component-segregated aerosols to trends in aerosol optical depth over land (2007–2019): Insights from CAMS aerosol reanalysis H. Zhao et al. https://doi.org/10.1016/j.atmosenv.2024.120676
- Cloud-based assessment of aerosol dynamics and population exposure in Southeast Asia using MERRA-2 and AERONET integration Z. Zheng et al. https://doi.org/10.1016/j.atmosenv.2026.121848
- Global hourly seamless AOD through measurement-adjusted machine learning fusion of multi-satellite and reanalysis data Y. Ding et al. https://doi.org/10.1080/15481603.2025.2586203
- How well are aerosol–cloud interactions represented in climate models? – Part 2: Isolating the aerosol impact on clouds following the 2014–2015 Holuhraun eruption G. Jordan et al. https://doi.org/10.5194/acp-25-13393-2025
- Assessing the performance of the Copernicus Atmosphere Monitoring Service reanalysis: a comprehensive analysis of aerosol optical depth over India K. Shukla et al. https://doi.org/10.1007/s11356-025-37286-3
- Evaluating CMIP6 models for CO2 and CH4 concentrations across Africa: performance, biases, and implications for climate predictions G. Magara et al. https://doi.org/10.1007/s00382-025-07679-8
- Effects of total cloud cover products on solar radiation estimation based on a radiation transfer model D. Pan et al. https://doi.org/10.1080/17538947.2025.2512608
- Diagnosing aerosol–meteorological interactions on snow within Earth system models: a proof-of-concept study over High Mountain Asia C. Roychoudhury et al. https://doi.org/10.5194/esd-16-1237-2025
Saved (final revised paper)
Latest update: 14 Jul 2026
Short summary
The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e., ensemble mean). The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where divergence and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e.,...
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