the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Long-term observations of cloud condensation nuclei over the Amazon rain forest – Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols
Mira L. Pöhlker
Florian Ditas
Jorge Saturno
Thomas Klimach
Isabella Hrabě de Angelis
Alessandro C. Araùjo
Joel Brito
Samara Carbone
Yafang Cheng
Xuguang Chi
Reiner Ditz
Sachin S. Gunthe
Bruna A. Holanda
Konrad Kandler
Jürgen Kesselmeier
Tobias Könemann
Ovid O. Krüger
Jošt V. Lavrič
Scot T. Martin
Eugene Mikhailov
Daniel Moran-Zuloaga
Luciana V. Rizzo
Diana Rose
Ryan Thalman
David Walter
Jian Wang
Stefan Wolff
Henrique M. J. Barbosa
Paulo Artaxo
Meinrat O. Andreae
Ulrich Pöschl
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Through the use of our machine-learning-based optical model, realistic BC morphologies can be incorporated into atmospheric science applications that require highly accurate results with minimal computational resources. The results of the study demonstrate that the predictions of single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved over the conventional Mie-based predictions when using the machine learning method.
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Aitken mode). Our study provides a general framework to estimate under which aerosol and cloud conditions Aitken mode particles affect clouds.
Through the use of our machine-learning-based optical model, realistic BC morphologies can be incorporated into atmospheric science applications that require highly accurate results with minimal computational resources. The results of the study demonstrate that the predictions of single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved over the conventional Mie-based predictions when using the machine learning method.
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accumulation mode). Previous studies suggest that this can also occur in smaller particles (
Aitken mode). Our study provides a general framework to estimate under which aerosol and cloud conditions Aitken mode particles affect clouds.
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