Detecting severe storms using an RGB composite combining polarimetric radar parameters

Besides reflectivity (Z) and radial velocity (V), polarimetric doppler radar provides much more information that is not often used by forecasters in real-time, at least in Europe. These data include among others the correlation coefficient (CC or RhoHV) and differential reflectivity (ZDR). By combining those data using the red, green and blue (RGB) color channels of an image these parameters can be combined in a visually pleasing way that contains a large amount of information. This idea was showcased by Trevor White (University of Alabama at Huntsville) who shared experimental images on social media. We think that this may be a way to make these polarimetric data more accessible to forecasters. 

At the ESSL Testbed 2025 we tested the composite product with forecasters. The composite that we provided to them has reflectivity (Z) increasing from 30 to 60 dBZ mapped onto the red channel, correlation coefficient decreasing from 1.0 to 0.7 onto the green channel, and differential reflectivity (ZDR) increasing from 0 to 8 onto the blue channel. The alpha (opacity) channel is used to emphasize higher reflectivity and reduces to fully transparent as reflectivity decreases from 43 to -10 dBZ in a piecewise linear way.  

The resulting RGB shows heavy rainfall as purple to magenta, hail as yellow or white, tornadic debris as green or yellow. Investigating the colors at various elevations can reveal details about the storm structure and microphysics, such as the vertical extent of hail in a storm. Although a storm can be studied using the individual parameters Z, ZDR, and CC, the RGB makes it easier. The method has some limitations, such as the fact that ground clutter can look similar to hail or tornadic debris, which can complicate the interpretation of the RGB.  

We will provide several examples and summarize the feedback from forecasters.