Zhe Feng — Pacific Northwest National Laboratory
Sally A. McFarlane — U.S. Department of Energy
Courtney Schumacher — Texas A&M University
Scott Mabry Ellis — National Center for Atmospheric Research (NCAR)
Nitin Bharadwaj — Pacific Northwest National Laboratory
Category
Field Campaigns
Description
Example of collocated time-height radar reflectivity from KAZR, S-Pol, and SMART-R on 28 October 2011 at the AMF site. (a) KAZR-ARSCL reflectivity, (b) S-Pol quality-controlled reflectivity, (c) SMART-R quality-controlled reflectivity, (d) surface rain rate from weighing bucket and present weather detector rain gauges, and microwave radiometer column liquid water path, (e) S-Pol raw reflectivity, (f) SMART-R raw reflectivity.
This study compares the measurements from the S-Pol and SMART-R radars to those from the more sensitive Ka-band ARM zenith radar (KAZR) during the Dynamics of the Madden-Julian Oscillation (DYNAMO)/ARM Madden-Julian Investigation Experiment (AMIE) field campaign in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars on Addu Atoll. Frequency comparisons for precipitating convective clouds and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds, and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar data set is produced to provide improved cloud boundary estimates, microphysics, and radiative heating retrievals.
