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Rosenfeld D, Zheng Y, Hashimshoni E, et al. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers. Proc Natl Acad Sci U S A. 2016;113(21):5828-34doi: 10.1073/pnas.1514044113.
Rosenfeld, D., Zheng, Y., Hashimshoni, E., Pöhlker, M. L., Jefferson, A., Pöhlker, C., Yu, X., Zhu, Y., Liu, G., Yue, Z., Fischman, B., Li, Z., Giguzin, D., Goren, T., Artaxo, P., Barbosa, H. M., Pöschl, U., & Andreae, M. O. (2016). Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers. Proceedings of the National Academy of Sciences of the United States of America, 113(21), 5828-34. https://doi.org/10.1073/pnas.1514044113
Rosenfeld, Daniel, et al. "Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers." Proceedings of the National Academy of Sciences of the United States of America vol. 113,21 (2016): 5828-34. doi: https://doi.org/10.1073/pnas.1514044113
Rosenfeld D, Zheng Y, Hashimshoni E, Pöhlker ML, Jefferson A, Pöhlker C, Yu X, Zhu Y, Liu G, Yue Z, Fischman B, Li Z, Giguzin D, Goren T, Artaxo P, Barbosa HM, Pöschl U, Andreae MO. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers. Proc Natl Acad Sci U S A. 2016 May 24;113(21):5828-34. doi: 10.1073/pnas.1514044113. Epub 2016 Mar 04. PMID: 26944081; PMCID: PMC4889349.
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Proc Natl Acad Sci U S A. 2016 May 24;113(21):5828-34. doi: 10.1073/pnas.1514044113. Epub 2016 Mar 04.

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers.

Proceedings of the National Academy of Sciences of the United States of America

Daniel Rosenfeld, Youtong Zheng, Eyal Hashimshoni, Mira L Pöhlker, Anne Jefferson, Christopher Pöhlker, Xing Yu, Yannian Zhu, Guihua Liu, Zhiguo Yue, Baruch Fischman, Zhanqing Li, David Giguzin, Tom Goren, Paulo Artaxo, Henrique M J Barbosa, Ulrich Pöschl, Meinrat O Andreae

Affiliations

  1. Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel; [email protected].
  2. Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20740; Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740; State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;
  3. Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel;
  4. Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz 55020, Germany; Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz 55020, Germany;
  5. Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305;
  6. Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz 55020, Germany;
  7. Meteorological Institute of Shaanxi Province, Xi'an 710015, China;
  8. State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Meteorological Institute of Shaanxi Province, Xi'an 710015, China;
  9. Physics Institute, University of Sao Paulo, Sao Paulo 05508-090, Brazil.

PMID: 26944081 PMCID: PMC4889349 DOI: 10.1073/pnas.1514044113

Abstract

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

Keywords: CCN concentrations; cloud−aerosol interactions; convective clouds; satellite remote sensing

References

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