Characterizing the ARSCL Product Record

 
Poster PDF

Authors

Eugene E. Clothiaux — Pennsylvania State University
Karen Lee Johnson — Brookhaven National Laboratory
Michael Jensen — Brookhaven National Laboratory
Pavlos Kollias — Stony Brook University
Tami Fairless — Pacific Northwest National Laboratory
Meng Wang — Brookhaven National Laboratory
Shannon Baxter — SUNY Geneseo

Category

General Topics – Cloud

Description

The Atmospheric Radiation Measurement (ARM) program continuously operated profiling Millimeter Cloud Radars (MMCRs) along with micropulse lidars and ceilometers at five fixed sites, for periods ranging from eight to nineteen years. At the Southern Great Plains and North Slope of Alaska sites, along with three Tropical Western Pacific sites, these observations have been synthesized using ARM's Active Remote Sensing of CLouds (ARSCL) value-added product, which provides cloud boundaries and best-estimate radar reflectivities, mean Doppler velocities and spectral widths. The product’s time resolution ranges from 10 seconds down to 4 seconds, with height resolution of 45 meters or better. The ARSCL data set, through its use in retrievals of cloud microphysics and dynamics, has the potential to make major contributions toward improved cloud representations in climate models and the understanding of cloud processes. However, it is essential that data set quality and accuracy be assessed and made available to data users in order to maximize utility and reliability. In this study, we apply a variety of approaches to characterize observation quality throughout the ARSCL data record at each site. We describe instrument availability and radar operating status and possible issues. We track radar sensitivity as a function of time through cirrus detection statistics as well as changes in radar signal saturation level over time. We also examine noise and insect clutter reflectivity levels as possible surrogates for radar calibration changes. Through these and other techniques, we assess the most and least reliable time periods for each instrumented site and provide valuable guidance to potential data users, for both case-study research and long-term climatological applications.