Radar is one of the most valuable tools in the Meteorologists toolkit – besides the standard reflectivity (which measures rainfall rates) and the relatively new dual-polarity functions that can help radars detect tornadic debris, one of the most vital and longest utilized tools is the “doppler” part of “doppler radar” – the doppler velocities. This tool measures wind speed of reflected objects relative to the radar, permitting the radar to see downbursts, rotation, cold fronts, and more. All and all though, sometimes it just seems like radar screens are just a bucket of spilled paint. Today, we’re going to take a look at how to interpret these colors, and how they work.
The first thing to understand is how it MEASURES the winds: the Doppler effect. You are familiar with this phenomenon, even if you don’t know it. When a siren passes by you, you almost certainly have noticed how, when it’s coming towards you, it’s high pitched, and as it drives away, it becomes noticeably low pitched. This is the doppler effect in action – as the motion of the object changes RELATIVE to you, the FREQUENCY of the sound or light waves coming towards you increases or decreases. This same phenomenon is responsible for doppler wind measurements – if a tornado is moving at 40mph, the frequency of the emitted beam is shifted DOWN because of the fact the object is moving away, thus taking longer for the beam to return. This is the core idea behind velocities, and this raw data is converted into blue and green color schemes.
Circling back to a real-world example, this tornado is easily visible on Radar, you just need to know what to look for when analyzing radar – remember, the wind measurements are all RELATIVE to the radar. GREEN shaded velocities indicate wind is moving towards the radar, and the brighter the green, the FASTER the motion is towards the radar. RED shaded velocities indicate wind moving AWAY from the radar, and likewise, the brighter the red, the faster the motion is away from the radar. Knowing these two crucial things open up a world of observational possibilities. Think about what a tornado is – a rapidly rotating column of air. Therefore, you should be looking for a very compact area of RED and GREEN in contact, as well as considerations as to how bright the colors are. This is called a couplet, and is often a predecessor or indicator to a tornado touching down. Without it, we’d truly be in the dark!
The possibilities don’t stop there, either – with velocities, you can also measure intense lines of wind, such as derechos. Take this example from Iowa in 2020, where a Derecho is moving through. You can see the substantial winds in green (and even blue, because they’re so intense!) moving TOWARDS the radar (the black dot), and you can see the initial gust front moving AWAY from the radar on the opposite side. With all of this in mind, hopefully you have the knowledge to know exactly what we’re talking about during severe weather coverage, if and when push comes to shove and we whip out our Doppler tools. But Radars use-cases don’t end there.
In more recent years, new tools have entered the radar users toolkit and have opened up a new dimension of radar analysis – literally. With the advent of what we call “dual-pol” in recent years, NEXRAD radars can now shoot out two different beams at two different angles, enabling the radar to process the three-dimensional shape of the objects it hits, from birds to bees to rain and hail, and interestingly enough, tornadic debris.
As intimidating as the term “Correlation Coefficient” sounds (typically abbreviated to just CC), it’s actually a fairly simple principle – think of it as a 0 to 100 scale, with closer to 100 (in red) indicating very similarly shaped objects being reflected by the radar, and closer to 0 (in greens and blues) indicating very peculiar, unusual objects being reflected by the radar. Early uses of this proved it useful in finding hail, but an interesting phenomena began occurring during tornado events; debris – be it glass, wood, or trees – actually was visible in the data. How exactly can you tell this, though? Let’s look at an example.
On April 28th, 2014, a significant tornado struck near Graysville, Alabama, just on the outskirts of Birmingham. Luckily, nobody was killed, but the tornado inflicted notable damage on nearby homes and structures. On radar, the presentation was clear – a large hook wrapped into the supercell, and velocities indicated high winds. At the time, CC was relatively new, however, and showed us what exactly was going on – an area of low CC (blue) surrounded by high CC (red). This indicated that, within the very similar, consistent mass of rain the supercell was producing, there were some very atypical, non-weather objects being lifted INTO the storm… and what does that? Tornadoes. Sure enough, the data proved to us that a tornado was ongoing, and this helped confirm the tornado which was rain-wrapped, moving fast, and occurring at night. Without this tool, the proper high-impact warnings may not have been issued, and indeed to this day may still elude us when tornadoes like this come around. Here in the southern US, they are often extremely difficult to see, so it goes without saying – CC can be a meteorologists best friend when confirmation is scant on the ground.
