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We have extensively analysed the interdependence between cloud opticaldepth, droplet effective radius, liquid water path (LWP) and geometricthickness for stratiform warm clouds using ground-based observations. Inparticular, this analysis uses cloud optical depths retrieved from untappedsolar background signals that are previously unwanted and need to be removedin most lidar applications. Combining these new optical depth retrievalswith radar and microwave observations at the Atmospheric RadiationMeasurement (ARM) Climate Research Facility in Oklahoma during 2005–2007,we have found that LWP and geometric thickness increase and follow apower-law relationship with cloud optical depth regardless of the presenceof drizzle; LWP and geometric thickness in drizzling clouds can be generally20–40% and at least 10% higher than those in non-drizzling clouds,respectively. In contrast, droplet effective radius shows a negativecorrelation with optical depth in drizzling clouds and a positivecorrelation in non-drizzling clouds, where, for large optical depths, itasymptotes to 10 μm. This asymptotic behaviour in non-drizzling cloudsis found in both the droplet effective radius and optical depth, making itpossible to use simple thresholds of optical depth, droplet size, or acombination of these two variables for drizzle delineation. This paperdemonstrates a new way to enhance ground-based cloud observations anddrizzle delineations using existing lidar networks

The interdependence of continental warm cloud properties derived from unexploited solar background signals in ground-based lidar measurements