Articles | Volume 22, issue 12
https://doi.org/10.5194/acp-22-8175-2022
© Author(s) 2022. 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-22-8175-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Aerosol atmospheric rivers: climatology, event characteristics, and detection algorithm sensitivities
Sudip Chakraborty
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Bin Guan
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Joint Institute for Regional Earth System Science and Engineering,
University of California, Los Angeles, CA, USA
Duane E. Waliser
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Arlindo M. da Silva
Global Modeling and Assimilation Office, NASA/Goddard Space Flight
Center, Greenbelt, MD, USA
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Cited
15 citations as recorded by crossref.
- A regionally refined quarter-degree global atmospheric rivers database based on ERA5 B. Guan & D. Waliser 10.1038/s41597-024-03258-4
- Number and size distribution of aerosols, and diurnal variation of radon progeny concentration during festival fireworks in Madikeri Town, Karnataka, India S. Namitha et al. 10.1016/j.nuclphysbps.2023.11.010
- Impact of increased anthropogenic Amazon wildfires on Antarctic Sea ice melt via albedo reduction S. Chakraborty et al. 10.1017/eds.2025.1
- Resilience to Air Pollution: A Novel Approach for Detecting and Predicting Aerosol Atmospheric Rivers within Earth System Boundaries K. Rautela et al. 10.1007/s41748-024-00421-0
- Modelling health implications of extreme PM2.5 concentrations in Indian sub-continent: Comprehensive review with longitudinal trends and deep learning predictions K. Rautela & M. Goyal 10.1016/j.techsoc.2025.102843
- Characterizing the spatio-temporal distribution, detection, and prediction of aerosol atmospheric rivers on a global scale K. Rautela et al. 10.1016/j.jenvman.2023.119675
- Spatio-temporal analysis of extreme air pollution and risk assessment K. Rautela & M. Goyal 10.1016/j.jenvman.2024.123807
- The Expanded Regulatory Significance of Saharan Dust Plumes in the United States P. Miller et al. 10.1021/acs.est.5c02205
- Impact of Canadian wildfires on aerosol and ice clouds in the early-autumn Arctic K. Sato et al. 10.1016/j.atmosres.2024.107893
- Polar Aerosol Atmospheric Rivers: Detection, Characteristics, and Potential Applications R. Lapere et al. 10.1029/2023JD039606
- Vertically resolved aerosol variability at the Amazon Tall Tower Observatory under wet-season conditions M. Franco et al. 10.5194/acp-24-8751-2024
- Unequal spatio-temporal distribution of population-weighted pollution extremes through deep learning K. Rautela et al. 10.1038/s41612-025-01183-w
- Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS) A. Collow et al. 10.5194/gmd-17-1443-2024
- Aerosol atmospheric rivers: patterns, impacts, and societal insights K. Rautela et al. 10.1007/s11356-024-34625-8
- Advances in tropical climatology – a review F. Moraes et al. 10.1080/02723646.2024.2313778
15 citations as recorded by crossref.
- A regionally refined quarter-degree global atmospheric rivers database based on ERA5 B. Guan & D. Waliser 10.1038/s41597-024-03258-4
- Number and size distribution of aerosols, and diurnal variation of radon progeny concentration during festival fireworks in Madikeri Town, Karnataka, India S. Namitha et al. 10.1016/j.nuclphysbps.2023.11.010
- Impact of increased anthropogenic Amazon wildfires on Antarctic Sea ice melt via albedo reduction S. Chakraborty et al. 10.1017/eds.2025.1
- Resilience to Air Pollution: A Novel Approach for Detecting and Predicting Aerosol Atmospheric Rivers within Earth System Boundaries K. Rautela et al. 10.1007/s41748-024-00421-0
- Modelling health implications of extreme PM2.5 concentrations in Indian sub-continent: Comprehensive review with longitudinal trends and deep learning predictions K. Rautela & M. Goyal 10.1016/j.techsoc.2025.102843
- Characterizing the spatio-temporal distribution, detection, and prediction of aerosol atmospheric rivers on a global scale K. Rautela et al. 10.1016/j.jenvman.2023.119675
- Spatio-temporal analysis of extreme air pollution and risk assessment K. Rautela & M. Goyal 10.1016/j.jenvman.2024.123807
- The Expanded Regulatory Significance of Saharan Dust Plumes in the United States P. Miller et al. 10.1021/acs.est.5c02205
- Impact of Canadian wildfires on aerosol and ice clouds in the early-autumn Arctic K. Sato et al. 10.1016/j.atmosres.2024.107893
- Polar Aerosol Atmospheric Rivers: Detection, Characteristics, and Potential Applications R. Lapere et al. 10.1029/2023JD039606
- Vertically resolved aerosol variability at the Amazon Tall Tower Observatory under wet-season conditions M. Franco et al. 10.5194/acp-24-8751-2024
- Unequal spatio-temporal distribution of population-weighted pollution extremes through deep learning K. Rautela et al. 10.1038/s41612-025-01183-w
- Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS) A. Collow et al. 10.5194/gmd-17-1443-2024
- Aerosol atmospheric rivers: patterns, impacts, and societal insights K. Rautela et al. 10.1007/s11356-024-34625-8
- Advances in tropical climatology – a review F. Moraes et al. 10.1080/02723646.2024.2313778
Latest update: 02 Nov 2025
Short summary
This study explores extreme aerosol transport events by aerosol atmospheric rivers (AARs) and shows the characteristics of individual AARs such as length, width, length-to-width ratio, transport strength, and dominant transport direction, the seasonal variations, the relationship to the spatial distribution of surface emissions, the vertical profiles of wind, aerosol mixing ratio, and aerosol mass fluxes, and the major planetary-scale aerosol transport pathways.
This study explores extreme aerosol transport events by aerosol atmospheric rivers (AARs) and...
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