Is the near-spherical shape the "new black" for smoke?

We examine the capability of near-sphericalshaped particles to reproduce the triple-wavelength particle linear depolarization ratio (PLDR) and lidar ratio (LR) values measured over Europe for stratospheric smoke originating from Canadian wildfires. The smoke layers were detected both in the troposph...

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Veröffentlicht in:Atmospheric chemistry and physics 2020-11, Vol.20 (22), p.14005-14021
Hauptverfasser: Gialitaki, Anna, Tsekeri, Alexandra, Amiridis, Vassilis, Ceolato, Romain, Paulien, Lucas, Kampouri, Anna, Gkikas, Antonis, Solomos, Stavros, Marinou, Eleni, Haarig, Moritz, Baars, Holger, Ansmann, Albert, Lapyonok, Tatyana, Lopatin, Anton, Dubovik, Oleg, Gross, Silke, Wirth, Martin, Tsichla, Maria, Tsikoudi, Ioanna, Balis, Dimitris
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Sprache:eng
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Zusammenfassung:We examine the capability of near-sphericalshaped particles to reproduce the triple-wavelength particle linear depolarization ratio (PLDR) and lidar ratio (LR) values measured over Europe for stratospheric smoke originating from Canadian wildfires. The smoke layers were detected both in the troposphere and the stratosphere, though in the latter case the particles presented PLDR values of almost 18 % at 532 nm as well as a strong spectral dependence from the UV to the near-IR wavelength. Although recent simulation studies of rather complicated smoke particle morphologies have shown that heavily coated smoke aggregates can produce large PLDR, herein we propose a much simpler model of compact near-spherical smoke particles. This assumption allows for the reproduction of the observed intensive optical properties of stratospheric smoke, as well as their spectral dependence. We further examine whether an extension of the current Aerosol Robotic Network (AERONET) scattering model to include the near-spherical shapes could be of benefit to the AERONET retrieval for stratospheric smoke cases associated with enhanced PLDR. Results of our study illustrate the fact that triple-wavelength PLDR and LR lidar measurements can provide us with additional insight when it comes to particle characterization.
ISSN:1680-7316
1680-7324
1680-7324
DOI:10.5194/acp-20-14005-2020