Can liquid cloud microphysical processes be used for cloud radar calibration?



Maahn, Maximilian — Leipzig University
de Boer, Gijs — University of Colorado

Area of research:

Cloud Processes

Journal Reference:

Maahn M, F Hoffmann, M Shupe, G de Boer, S Matrosov, and E Luke. 2019. "Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?" Atmospheric Measurement Techniques, 12(6), doi:10.5194/amt-12-3151-2019.


Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Here, we present three novel methods for calibrating vertically pointing cloud radars. These calibration methods are based on microphysical processes of liquid clouds, such as the transition of cloud droplets to drizzle drops.


We successfully apply the methods to cloud radar data from the North Slope of Alaska (NSA) and Oliktok Point (OLI) U.S. Department of Energy Atmospheric Radiation Measurement (ARM) sites. Because the method can be applied to past data sets, it can be used to evaluate and – if necessary – repair past cloud radar data sets.


Thus far, no single robust method exists for assessing the calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes in liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). For each relation, we evaluate the potential for radar calibration. For γ and W, we use state-of-the-art Lagrangian microphysics box model simulations to determine typical radar reflectivity values for reference points. We apply the new methods to observations at the ARM sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that liquid cloud processes are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that, in 2016, the radar reflectivity at NSA was about 1±1 dB too low but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.