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Titel |
Retrieval of ice crystals’ mass from ice water content and particle distribution measurements: a numerical optimization approach |
VerfasserIn |
Pierre Coutris, Delphine Leroy, Emmanuel Fontaine, Alfons Schwarzenboeck, J. Walter Strapp |
Konferenz |
EGU General Assembly 2016
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 18 (2016) |
Datensatznummer |
250123381
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Publikation (Nr.) |
EGU/EGU2016-2621.pdf |
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Zusammenfassung |
A new method to retrieve cloud water content from in-situ measured 2D particle images from
optical array probes (OAP) is presented. With the overall objective to build a statistical model
of crystals’ mass as a function of their size, environmental temperature and crystal
microphysical history, this study presents the methodology to retrieve the mass of crystals
sorted by size from 2D images using a numerical optimization approach. The methodology is
validated using two datasets of in-situ measurements gathered during two airborne field
campaigns held in Darwin, Australia (2014), and Cayenne, France (2015), in the frame of the
High Altitude Ice Crystals (HAIC) / High Ice Water Content (HIWC) projects. During these
campaigns, a Falcon F-20 research aircraft equipped with state-of-the art microphysical
instrumentation sampled numerous mesoscale convective systems (MCS) in order to study
dynamical and microphysical properties and processes of high ice water content
areas.
Experimentally, an isokinetic evaporator probe, referred to as IKP-2, provides a reference
measurement of the total water content (TWC) which equals ice water content, (IWC)
when (supercooled) liquid water is absent. Two optical array probes, namely 2D-S
and PIP, produce 2D images of individual crystals ranging from 50 μm to 12840
μm from which particle size distributions (PSD) are derived. Mathematically, the
problem is formulated as an inverse problem in which the crystals’ mass is assumed
constant over a size class and is computed for each size class from IWC and PSD
data:
PSD.m = IW C
This problem is solved using numerical optimization technique in which an objective
function is minimized. The objective function is defined as follows:
2
J(m )=∥P SD.m − IW C ∥ + λ.R (m)
where the regularization parameter λ and the regularization function R(m) are tuned
based on data characteristics.
The method is implemented in two steps. First, the method is developed on synthetic
crystal populations in order to evaluate the behavior of the iterative algorithm, the
influence of data noise on the quality of the results, and to set up a regularization
strategy. Therefore, 3D synthetic crystals have been generated and numerically
processed to recreate the noise caused by 2D projections of randomly oriented 3D
crystals and by the discretization of the PSD into size classes of predefined width.
Subsequently, the method is applied to the experimental datasets and the comparison
between the retrieved TWC (this methodology) and the measured ones (IKP-2 data)
will enable the evaluation of the consistency and accuracy of the mass solution
retrieved by the numerical optimization approach as well as preliminary assessment
of the influence of temperature and dynamical parameters on crystals’ masses. |
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