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A satellite view of aerosols in the climate system

Author

Listed:
  • Yoram J. Kaufman

    (NASA/Goddard Space Flight Center)

  • Didier Tanré

    (Laboratoire d'Optique Atmosphérique, Université de Lille/CNRS)

  • Olivier Boucher

    (Laboratoire d'Optique Atmosphérique, Université de Lille/CNRS)

Abstract

Anthropogenic aerosols are intricately linked to the climate system and to the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Depending on their composition, aerosols can also absorb sunlight in the atmosphere, further cooling the surface but warming the atmosphere in the process. These effects of aerosols on the temperature profile, along with the role of aerosols as cloud condensation nuclei, impact the hydrologic cycle, through changes in cloud cover, cloud properties and precipitation. Unravelling these feedbacks is particularly difficult because aerosols take a multitude of shapes and forms, ranging from desert dust to urban pollution, and because aerosol concentrations vary strongly over time and space. To accurately study aerosol distribution and composition therefore requires continuous observations from satellites, networks of ground-based instruments and dedicated field experiments. Increases in aerosol concentration and changes in their composition, driven by industrialization and an expanding population, may adversely affect the Earth's climate and water supply.

Suggested Citation

  • Yoram J. Kaufman & Didier Tanré & Olivier Boucher, 2002. "A satellite view of aerosols in the climate system," Nature, Nature, vol. 419(6903), pages 215-223, September.
  • Handle: RePEc:nat:nature:v:419:y:2002:i:6903:d:10.1038_nature01091
    DOI: 10.1038/nature01091
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    Citations

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    Cited by:

    1. Yumara Martín-Cruz & Álvaro Gómez-Losada, 2023. "Risk Assessment and Source Apportionment of Metals on Atmospheric Particulate Matter in a Suburban Background Area of Gran Canaria (Spain)," IJERPH, MDPI, vol. 20(10), pages 1-18, May.
    2. Wei Wang & Zengxin Pan & Feiyue Mao & Wei Gong & Longjiao Shen, 2017. "Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements," IJERPH, MDPI, vol. 14(9), pages 1-12, September.
    3. Suman Moparthy & Dominique Carrer & Xavier Ceamanos, 2019. "Can We Detect the Brownness or Greenness of the Congo Rainforest Using Satellite-Derived Surface Albedo? A Study on the Role of Aerosol Uncertainties," Sustainability, MDPI, vol. 11(5), pages 1-21, March.
    4. Cheng Chen & Oleg Dubovik & Gregory L. Schuster & Mian Chin & Daven K. Henze & Tatyana Lapyonok & Zhengqiang Li & Yevgeny Derimian & Ying Zhang, 2022. "Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    5. Neha Shaw & A. K. Gorai, 2020. "Study of aerosol optical depth using satellite data (MODIS Aqua) over Indian Territory and its relation to particulate matter concentration," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(1), pages 265-279, January.
    6. B. Padmakumari & A. Jaswal & B. Goswami, 2013. "Decrease in evaporation over the Indian monsoon region: implication on regional hydrological cycle," Climatic Change, Springer, vol. 121(4), pages 787-799, December.
    7. Tianhao Zhang & Gang Liu & Zhongmin Zhu & Wei Gong & Yuxi Ji & Yusi Huang, 2016. "Real-Time Estimation of Satellite-Derived PM 2.5 Based on a Semi-Physical Geographically Weighted Regression Model," IJERPH, MDPI, vol. 13(10), pages 1-13, September.
    8. Brigitte Mueller & Xuebin Zhang, 2016. "Causes of drying trends in northern hemispheric land areas in reconstructed soil moisture data," Climatic Change, Springer, vol. 134(1), pages 255-267, January.
    9. Xiankang Xu & Kaifang Shi & Zhongyu Huang & Jingwei Shen, 2023. "What Factors Dominate the Change of PM 2.5 in the World from 2000 to 2019? A Study from Multi-Source Data," IJERPH, MDPI, vol. 20(3), pages 1-28, January.
    10. Tianhao Zhang & Wei Gong & Wei Wang & Yuxi Ji & Zhongmin Zhu & Yusi Huang, 2016. "Ground Level PM 2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO 2 and Enhanced Vegetation Index (EVI)," IJERPH, MDPI, vol. 13(12), pages 1-12, December.
    11. Xiang-Dong Chen & En-Hui Wang & Long-Kun Shan & Shao-Chun Zhang & Ce Feng & Yu Zheng & Yang Dong & Guang-Can Guo & Fang-Wen Sun, 2023. "Quantum enhanced radio detection and ranging with solid spins," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    12. Liang Cheng & Long Li & Longqian Chen & Sai Hu & Lina Yuan & Yunqiang Liu & Yifan Cui & Ting Zhang, 2019. "Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period," IJERPH, MDPI, vol. 16(19), pages 1-25, September.
    13. Prasad, Abhnil Amtesh & Nishant, Nidhi & Kay, Merlinde, 2022. "Dust cycle and soiling issues affecting solar energy reductions in Australia using multiple datasets," Applied Energy, Elsevier, vol. 310(C).
    14. Zhiyuan Fang & Hao Yang & Ye Cao & Kunming Xing & Dong Liu & Ming Zhao & Chenbo Xie, 2021. "Study of Persistent Pollution in Hefei during Winter Revealed by Ground-Based LiDAR and the CALIPSO Satellite," Sustainability, MDPI, vol. 13(2), pages 1-14, January.

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