Remote sensing of cloud sides of deep convection: towards a three-dimensional retrieval of cloud particle size profiles T. Zinner1,2, A. Marshak1, S. Lang3, J. V. Martins1,4, and B. Mayer2 1NASA – Goddard Space Flight Center, Climate and Radiation Branch, Greenbelt, MD, USA 2Deutsches Zentrum für Luft- und Raumfahrt, Inst. für Physik der Atmosphäre, Oberpfaffenhofen, 82230 Wessling, Germany 3NASA – Goddard Space Flight Center, Mesoscale Atmospheric Processes Branch, Greenbelt and Science Systems and Applications Inc., Lanham, MD, USA 4Department of Physics and Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD, USA
Abstract. 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
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.
Citation: Zinner, T., Marshak, A., Lang, S., Martins, J. V., and Mayer, B.: Remote sensing of cloud sides of deep convection: towards a three-dimensional retrieval of cloud particle size profiles, Atmos. Chem. Phys., 8, 4741-4757, doi:10.5194/acp-8-4741-2008, 2008.