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Proceedings Paper

Predicting atmospheric aerosol size distributions using Mixture Density Networks
Author(s): Joshua J. Rudiger; John Stephen deGrassie; Kevin McBryde; Stephen Hammel
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Paper Abstract

We use Mixture Density Networks (MDN) to estimate atmospheric particle size distributions based upon metrological parameters. Measurements of particle size spectra show that distributions are often multi-modal, composed of various underlying aerosol species that can grow from one mode to another. The flexibility of the MDN allows for the prediction of an arbitrary distribution. We show here that the MDN prediction engine can be useful in forecasting complicated, multi-modal particle size distributions. To inform and train the MDN we use meteorological, particle size and optical extinction measurements taken from a three week propagation measurement field campaign.

Paper Details

Date Published: 4 September 2015
PDF: 7 pages
Proc. SPIE 9614, Laser Communication and Propagation through the Atmosphere and Oceans IV, 96140M (4 September 2015); doi: 10.1117/12.2189931
Show Author Affiliations
Joshua J. Rudiger, SPAWAR Systems Ctr. Pacific (United States)
John Stephen deGrassie, SPAWAR Systems Ctr. Pacific (United States)
Kevin McBryde, SPAWAR Systems Ctr. Pacific (United States)
Stephen Hammel, SPAWAR Systems Ctr. Pacific (United States)


Published in SPIE Proceedings Vol. 9614:
Laser Communication and Propagation through the Atmosphere and Oceans IV
Alexander M. J. van Eijk; Christopher C. Davis; Stephen M. Hammel, Editor(s)

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