Issue |
EPJ Web of Conferences
Volume 119, 2016
The 27th International Laser Radar Conference (ILRC 27)
|
|
---|---|---|
Article Number | 23022 | |
Number of page(s) | 4 | |
Section | Poster Session (Aerosol Observations and Retrievals II) | |
DOI | https://doi.org/10.1051/epjconf/201611923022 | |
Published online | 07 June 2016 |
https://doi.org/10.1051/epjconf/201611923022
Combined sphere-spheroid particle model for the retrieval of the microphysical aerosol parameters via regularized inversion of lidar data
1 University of Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany
2
Laser Remote Sensing Department, National Institute of R&D for Optoelectronics, 409 Atomistilor Str., Magurele, Ilfov, Romania
* samaras@uni-potsdam.de
** bockmann@rz.uni-potsdam.de
*** nnicol@inoe.ro
Published online: 7 June 2016
In this work we propose a two-step advancement of the Mie spherical-particle model accounting for particle non-sphericity. First, a naturally two-dimensional (2D) generalized model (GM) is made, which further triggers analogous 2D re-definitions of microphysical parameters. We consider a spheroidal-particle approach where the size distribution is additionally dependent on aspect ratio. Second, we incorporate the notion of a sphere-spheroid particle mixture (PM) weighted by a non-sphericity percentage. The efficiency of these two models is investigated running synthetic data retrievals with two different regularization methods to account for the inherent instability of the inversion procedure. Our preliminary studies show that a retrieval with the PM model improves the fitting errors and the microphysical parameter retrieval and it has at least the same efficiency as the GM. While the general trend of the initial size distributions is captured in our numerical experiments, the reconstructions are subject to artifacts. Finally, our approach is applied to a measurement case yielding acceptable results.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.