Determination of three‐dimensional cloud structures from high‐resolution radiance data

Abstract

[1] The three-dimensional structure and the inhomogeneity of clouds pose a field of challenges. The characterization of their spatial structure, their microphysical properties, and their variability is difficult. This kind of knowledge is crucial to any investigation on the impact of clouds on the radiation budget or on the reliability of cloud remote sensing data. In this article the characteristics of radiation transport in inhomogeneous clouds are studied using three-dimensional (3-D) simulations of radiative transport and the independent pixel approximation (IPA). The opposing effects of radiative smoothing and sharpening due to horizontal photon transport are examined in terms of the Green's function, which describes the interrelation of the radiance fields calculated using IPA and 3-D radiative transport. On the basis of these considerations a novel method was developed for the retrieval of realistic 3-D stratocumulus structures from high-spatialresolution radiance fields observed by a compact airborne spectrographic imager (CASI, 15 m resolution). An initial distribution of liquid water content and effective droplet size retrieved using the IPA assumption and an adiabatic microphysical model is iteratively adjusted with the objective of matching the observation by the 3-D forward radiative transfer simulation for the derived cloud. For the iterative adjustment an approximate Green's function is utilized to remove 3-D effects from the observation. The performance of the method is characterized by application to a known cloud structure and by comparison of the derived cloud properties to in situ data from various field campaigns. The method provides the ideal basis for our studies on the remote sensing of inhomogeneous clouds.Citation: Zinner, T., B. Mayer, and M. Schröder (2006), Determination of three-dimensional cloud structures from high-resolution radiance data,

Solar zenith and viewing geometry‐dependent errors in satellite retrieved cloud optical thickness: Marine stratocumulus case

“…In this approach, clouds fields were obtained in several different ways. For example, Zuidema and Evans [1998] retrieved cloud fields from a ground‐based radar and a microwave radiometer, Kato et al [2006] used cloud fields generated by a cloud model, and Zinner and Mayer [2006] obtained the 3d cloud structure from airborne radiance observations using a retrieval technique developed by Zinner et al [2006]. The advantage of this approach is that the true cloud optical thickness is known and the exact error can be accurately estimated.…”

Radiative transfer in the cloudy atmosphere

“…3D radiative transfer is required for applications like the high-resolution remote sensing of clouds, the effect of topography on the radiation budget, the cloud-radiation interaction in cloud-resolving models, or the passive remote sensing of inhomogeneous surfaces, to name but a few. While 3D radiative transfer has been mainly used to quantify the uncertainty of 1D approximations historically, current applications also concentrate on directly applying 3D radiative transfer, e.g., in the high-resolution remote sensing of clouds [18,19]. Playing around with a Monte Carlo model helps students get real insight into the processes which affect solar and thermal radiation on their complex path through the atmosphere.…”

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

“…Obvious products will be cloud cover and cloud-size distributions. In addition, the use of three-dimensional radiative transfer methods will permit to retrieve cloud optical thickness, droplet radius, and cloud top structure with high spatial resolution (Mayer 2009;Zinner et al 2006) and may even be able to distinguish the cloud-core area from the optically thinner edges. The contribution of clouds to solar heating and infrared cooling rates will also be estimated from these parameters.…”