Abstract
Abstract. Clouds are one of the main reasons of uncertainties in the forecasts of weather and climate. In part, this is due to limitations of remote sensing of cloud microphysics. Present approaches often use passive spectral measurements for the remote sensing of cloud microphysical parameters. Large uncertainties are introduced by three-dimensional (3-D) radiative transfer effects and cloud inhomogeneities. Such effects are largely caused by unknown orientation of cloud sides or by shadowed areas on the cloud. Passive ground-based remote sensing of cloud properties at high spatial resolution could be crucially improved with this kind of additional knowledge of cloud geometry. To this end, a method for the accurate reconstruction of 3-D cloud geometry from cloud radar measurements is developed in this work. Using a radar simulator and simulated passive measurements of model clouds based on a large eddy simulation (LES), the effects of different radar scan resolutions and varying interpolation methods are evaluated. In reality, a trade-off between scan resolution and scan duration has to be found as clouds change quickly. A reasonable choice is a scan resolution of 1 to 2\\degree. The most suitable interpolation procedure identified is the barycentric interpolation method. The 3-D reconstruction method is demonstrated using radar scans of convective cloud cases with the Munich miraMACS, a 35 GHz scanning cloud radar. As a successful proof of concept, camera imagery collected at the radar location is reproduced for the observed cloud cases via 3-D volume reconstruction and 3-D radiative transfer simulation. Data sets provided by the presented reconstruction method will aid passive spectral ground-based measurements of cloud sides to retrieve microphysical parameters.
Highlights
Clouds play an essential role in Earth’s climate due to their impact on Earth’s radiation budget
In order to consider these challenges, several interpolation methods and parameters were tested in the controlled environment of the large eddy simulation (LES) cloud case: nearest-neighbour interpolation (NNE), inverse distance weighting (IDW) (Shepard, 1968), barycentric interpolation (BAR) (Möbius, 1976) and natural neighbour interpolation (NAT) (Sibson, 1981)
The analysis showed that for radiance field reconstructions, the choice of scan resolution clearly overrides the choice of interpolation method
Summary
Clouds play an essential role in Earth’s climate due to their impact on Earth’s radiation budget. In recent studies, Fielding et al (2013, 2014) have worked out ways to retrieve the 3-D field of LWC (liquid water content) to address the problem of 3-D clouds in radiation closure measurements at the surface To this end they conducted numerical studies to find suitable scan strategies for a successful reconstruction of the 3-D LWC field. This study will complement the previous work of Fielding et al (2013) in its aim to analyse the impact of scan resolution and interpolation methods on the reconstruction of a LWC field for one specific cloud It differs from the approach of Fielding et al (2014) in that LWC and the effective radius are not completely reconstructed on the basis of cloud radar measurements alone.
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