This evening, the Chicago area looked to be just on the northern edge of a shield of precipitation over much of the Ohio River Valley. In fact, the base reflectivity looked like this around 5:30 PM CST:
You'll notice a wide area of rather light reflectivity, including a large area of light returns to the east of the radar. The radar was scanning in a pattern called VCP 31, which is one of the most sensitive scanning patterns the radar can use. This scanning pattern is most often used in clear air situations (when there's not much to look at) or in the case of snow events, since snow tends to have a lower reflectivity than liquid rain. Anyhow, one might ask what kind of precipitation we are looking at here. If we assume that the radar beam is propagating normally, then we can guess that the area of light returns to the east of the radar runs from about 10000-15000 feet above ground. Let's take a look at the RUC forecast sounding from that time:
So now that we have a little bit of confidence in that model sounding, our overall confidence in the model increases. Let's take a look at what the model forecasts the sounding to be around an hour later.
And then again an hour later:
We can see that just as the model was predicting, that layer seemed to dry out quite considerably. By two hours later, there is very little precipitation left in that area to the east of the radar. If you were to watch the full loop, you'd see it actually eroded from the south to the north, so the ice crystals didn't simply advect away. They either sublimated or fell out. Regardless, this seems to confirm the model's forecast of drying in that layer.
But we can do better than that with our radars now. The Chicago radar is one of the few in the nation that has been upgraded to have dual-polarization. Now, I haven't talked a whole lot about what dual-polarization means on this blog (though I plan to in the near future), but there are some simple things that I can go over right now to illustrate the new capabilities this adds to the radar.
With dual-polarization, the radar scans with two different beams of two different orientations--one is sensitive to returns in the horizontal direction and another is sensitive to returns in the vertical direction. This allows us to get a good idea of the relative shape of what the radar is looking at. We can most directly see this in a product known as differential reflectivity or ZDR. This simply takes the magnitude of the vertical return and subtracts it from the magnitude of the horizontal return.
Let's imagine we're looking at small raindrops, like in drizzle. Small raindrops tend to be nearly spherical.
However, let's think about big, dendritic snowflakes. You know, the six-ponted, fancy kind you imagine snowflakes to be. It turns out when those flakes fall, they tend to fall with their big, flat side facing the ground. Now let's think about with this means in terms of differential reflectivity (ZDR).
Now, let's pretend we knew nothing about the temperature structure of the atmosphere at the time of the first radar image I showed above. We saw that area of very light returns to the east of the radar and knew it could either be one of two things--either light rain/drizzle or snow. Reflectivity doesn't tell us, but ZDR can give us a clue. Here's the ZDR image for that time:
Notice in that area to the east of the radar, there's a lot of green and yellow. Going over to our color scale on the left side of the image, we see that that points to ZDR values of 1-2 dB--positive values! We don't see any blue, which we would expect to see at least some of if the ZDR values were near zero. Because we're seeing fairly robust positive values for ZDR and knowing what we know about how ZDR relates to hydrometeor shape, we could assume that what we're seeing here is all snow. It turns out that dendritic crystals like to form in temperature between -12 to -18 degrees Celsius. Returning to our model sounding, we can see that the temperatures in the saturated layer do indeed overlap with that dendritic crystal temperature range (that range is highlighted where the red temperature trace in the image below becomes yellow). So, the radar's indication of hydrometeor type matches the model sounding's guess.
So, let's look at the correlation coefficient map for this time.
So there we see a simple case where the addition of dual-pol products helps us to glean a lot more from a radar image than just what reflectivity alone may tell us. The radar can be used to qualitatively verify model forecast soundings to be sure that what the model is telling us is what's actually happening. We can also use the model soundings to help inform us as to what we're seeing on radar, letting us make better short-term forecasts of precipitation type.