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| Titel |
Remote sensing of cloud sides of deep convection: towards a three-dimensional retrieval of cloud particle size profiles |
| VerfasserIn |
T. Zinner, A. Marshak, S. Lang, J. V. Martins, B. Mayer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 8, no. 16 ; Nr. 8, no. 16 (2008-08-18), S.4741-4757 |
| Datensatznummer |
250006330
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| Publikation (Nr.) |
 copernicus.org/acp-8-4741-2008.pdf |
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| Zusammenfassung |
The cloud scanner sensor is a central part of a recently proposed satellite
remote sensing concept – the three-dimensional (3-D) cloud and aerosol
interaction mission (CLAIM-3D) combining measurements of aerosol
characteristics in the vicinity of clouds and profiles of cloud microphysical
characteristics. Such a set of collocated measurements will allow new
insights in the complex field of cloud-aerosol interactions affecting
directly the development of clouds and precipitation, especially in
convection. The cloud scanner measures radiance reflected or emitted by cloud
sides at several wavelengths to derive a profile of cloud particle size and
thermodynamic phase. For the retrieval of effective size a Bayesian approach
was adopted and introduced in a preceding paper.
In this paper the potential of the approach, which has to account for the
complex three-dimensional nature of cloud geometry and radiative transfer, is
tested in realistic cloud observing situations. In a fully simulated
environment realistic cloud resolving modelling provides complex 3-D
structures of ice, water, and mixed phase clouds, from the early stage of
convective development to mature deep convection. A three-dimensional Monte
Carlo radiative transfer is used to realistically simulate the aspired
observations.
A large number of cloud data sets and related simulated observations provide
the database for an experimental Bayesian retrieval. An independent
simulation of an additional cloud field serves as a synthetic test bed for
the demonstration of the capabilities of the developed retrieval techniques.
For this test case only a minimal overall bias in the order of 1% as well as
pixel-based uncertainties in the order of 1 μm for droplets and 8 μm for ice
particles were found for measurements at a high spatial resolution of 250 m. |
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