Articles | Volume 14, issue 2
Atmos. Meas. Tech., 14, 1743–1759, 2021
Atmos. Meas. Tech., 14, 1743–1759, 2021

Research article 03 Mar 2021

Research article | 03 Mar 2021

A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

Xiaoyu Hu et al.

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Cited articles

Abrol, D. P.: Diversity of pollinating insects visiting litchi flowers (Litchi chinensis Sonn.) and path analysis of environmental factors influencing foraging behaviour of four honeybee species, J. Apicult. Res., 45, 180–187,, 2015. 
Arulraj, M. and Barros, A. P.: Shallow Precipitation Detection and Classification Using Multifrequency Radar Observations and Model Simulations, J. Atmos. Ocean. Tech., 34, 1963–1983,, 2017. 
Bala, G., Caldeira, K., Nemani, R., Cao, L., Ban-Weiss, G., and Shin, H.-J.: Albedo enhancement of marine clouds to counteract global warming: impacts on the hydrological cycle, Clim. Dynam., 37, 915–931,, 2010. 
Baldini, L. and Gorgucci, E.: Identification of the Melting Layer through Dual-Polarization Radar Measurements at Vertical Incidence, J. Atmos. Ocean. Tech., 23, 829–839,, 2006. 
Short summary
Cloud radars are powerful instruments that can probe detailed cloud structures. However, radar echoes in the lower atmosphere are always contaminated by clutter. We proposed a multi-dimensional probability distribution function that can effectively discriminate low-level clouds from clutter by considering their different features in several variables. We applied this method to the radar observations at the SACOL site and found the results have good agreement with lidar detection.