An algorithm for retrieval of cloud microphysics using 95‐GHz cloud radar and lidar

Abstract

[1] We develop a new forward algorithm for the retrieval of effective size and ice water content (IWC) of ice crystals in clouds by using collocated 95-GHz (3.16 mm) cloud radar and lidar with the wavelength of 0.532 mm. Use of radar or lidar alone has a fundamental difficulty to obtain cloud microphysics because of the wide variety of size distributions of cloud particles, though it is effective to obtain cloud macrophysical information such as cloud boundaries. The combined use of radar and lidar can overcome this problem. One unique feature of the algorithm is the attenuation-correction to the lidar signals according to the cloud microphysics determined by look-up tables of backscattering and extinction for the radar and lidar signals. Consequently, the combined system enables the retrieval of vertical profiles of the effective radius (r eff ) and ice water content (IWC). We perform several numerical analyses of the retrieved values for potential sources of errors, that is, the shape of the size distribution, biases in the radar and lidar signals, and the effect of multiple scattering. Then we provide the formulations that describe the retrieval errors as a function of the given bias and optical thickness. Finally, we demonstrate retrieval of microphysics for ground-based observation of cirrus clouds in February 2000 in Kashima, Japan. We examine the vertical distributions of r eff , IWC, fall velocity, and depolarization ratio as well as the interrelationships between them. The radius of the particles turns out to be the largest near the cloud bottom, and the fall velocity also shows a trend consistent with the r eff tendency. There are no in situ measurements to validate the retrieved parameters for the observations. Instead, supporting arguments are given on the basis of information about the expected behavior of the relationships between the cloud microphysical parameters from the literature.

G band atmospheric radars: new frontiers in cloud physics

“…Benedetti et al, 2003;Austin et al, 2009), radar-lidar (e.g. Donovan andvan Lammeren, 2001;Wang and Sassen, 2002;Okamoto et al, 2003;Hogan, 2008, 2010) and radar Doppler based techniques (e.g. Matrosov et al, 2002;Mace et al, 2002;Delanoë et al, 2007;Szyrmer et al, 2012).…”

Comparison of high‐level clouds represented in a global cloud system–resolving model with CALIPSO/CloudSat and geostationary satellite observations

“…Among them, the use of split window is effective to detect long-lasting cirrus clouds from geostationary satellite data, since no visible data are required. Lidar observation is also considered a powerful tool to detect cirrus clouds and to retrieve the optical properties of cirrus clouds [e.g., Platt, 1979;Sassen et al, 1990;Mace et al, 1998a;Okamoto et al, 2003]. With the launch of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CA-LIPSO) and CloudSat, we now have a significant amount of new-generation observations for the vertical structure of cloud and aerosol from space.…”

Ice clouds microphysical retrieval using 94‐GHz Doppler radar observations: Basic relations within the retrieval framework

“…Subsequently, several algorithms that utilize ground-based and space-based active remote sensing have been proposed for the retrieval of ice cloud microphysical properties. Most of the proposed algorithms can be classified in radar-only [e.g., Benedetti et al, 2003;Austin et al, 2009], radar-lidar [e.g., Donovan and van Lammeren, 2001;Wang and Sassen, 2002;Okamoto et al, 2003;Delanoё andHogan, 2008, 2010] and radar -Doppler based techniques [e.g., Matrosov et al, 2002;Mace et al, 2002;Delanoё et al, 2007], or both lidar and multiparameter radar [Sato et al, 2009]. Extensive reviews on existing algorithms and their performance can be found in Heymsfield et al [2008], Protat et al [2010] and Stein et al [2011].…”