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.
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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Cited
5 citations as recorded by crossref.
- 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. 10.1016/j.atmosenv.2024.120676
- Evaluating CMIP6 models for CO2 and CH4 concentrations across Africa: performance, biases, and implications for climate predictions G. Magara et al. 10.1007/s00382-025-07679-8
- Aircraft engine dust ingestion at global airports C. Ryder et al. 10.5194/nhess-24-2263-2024
- Atmospheric aerosols in the South Pacific: A regional baseline and characterization of aerosol fractions A. Isaza et al. 10.1016/j.atmosenv.2025.121048
- The 2024 report of the Lancet Countdown on health and climate change: facing record-breaking threats from delayed action M. Romanello et al. 10.1016/S0140-6736(24)01822-1
5 citations as recorded by crossref.
- 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. 10.1016/j.atmosenv.2024.120676
- Evaluating CMIP6 models for CO2 and CH4 concentrations across Africa: performance, biases, and implications for climate predictions G. Magara et al. 10.1007/s00382-025-07679-8
- Aircraft engine dust ingestion at global airports C. Ryder et al. 10.5194/nhess-24-2263-2024
- Atmospheric aerosols in the South Pacific: A regional baseline and characterization of aerosol fractions A. Isaza et al. 10.1016/j.atmosenv.2025.121048
- The 2024 report of the Lancet Countdown on health and climate change: facing record-breaking threats from delayed action M. Romanello et al. 10.1016/S0140-6736(24)01822-1
Latest update: 06 Jun 2025
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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