Scanning ARM cloud radar value-added products: the first generation
Authors
Karen Lee Johnson — Brookhaven National Laboratory
Pavlos Kollias — Stony Brook University
Ieng Jo — McGill University
Paloma Borque — Pacific Northwest National Laboratory
Aleksandra Tatarevic — McGill University
David T. Troyan — Brookhaven National Laboratory
Scott Giangrande — Brookhaven National Laboratory
Michael Jensen — Brookhaven National Laboratory
Category
Cloud Properties
Description
ARM has extended its long-time vertically profiling cloud radar observation capabilities into three dimensions with the installation of the Ka-, W-, and X-band scanning ARM cloud radars (SACRs) at its facilities, creating the first such continuously operating network. Scanning strategies have been developed to provide scientifically meaningful coverage of cloud and precipitation targets. The next step required to leverage scanning cloud radar observations into meaningful cloud and precipitation research is the development of quality-controlled value-added products (VAPs).Here we focus primarily on the first generation of SACR-based VAPs, which are currently under development. This set of products provides feature masking and correction of moments from the individual radars. We discuss the relevant algorithms and provide examples of the expected products. A primary product is the significant feature mask. A robust masking algorithm differentiates hydrometeors and other significant returns (insects, ground clutter, second trip echoes) from radar receiver noise. In general, the SACR noise floor is determined adaptively, radial-by-radial, to account for environmental fluctuations and hardware issues. However, the masking procedure does rely on a climatologically determined maximum noise value to handle cases where atmospheric returns are present throughout most or all of a radial's range gates. Nearest-in-time soundings are incorporated into the VAP to enable the estimation of water vapor attenuation and perform the associated reflectivity corrections. Sounding-derived winds are used as a first guess of horizontal winds in the unfolding of aliased mean Doppler velocities. At the Southern Great Plains site, an algorithm based on linear depolarization ratio, temperature, and ceilometer cloud-base heights is employed in the lowest few kilometers to differentiate hydrometeor and insect returns.
Examples of these products are displayed, and plans for additional SACR products are discussed. Among these are horizontal wind retrievals using the hemispherical-sky range height indicator scans and the gridding of scanning cloud radar moments.