Morse Code of Weather: how dual-polarization weather radar helps meteorologists pinpoint severe weather

Published: Jul. 20, 2022 at 1:46 AM CDT
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BISMARCK, N.D. (KFYR) - Last week, we talked about velocity mode on weather radars and how that allows us to see inside thunderstorms to detect the speed and direction of precipitation. With severe weather, this allows us to see the rotation within thunderstorms to detect where tornadoes may form and we can also see where damaging straight-line winds may be within storms. The reflectivity mode of weather radars is what you commonly see when you load up your weather app or see radar on television — this simply shows the intensity of the precipitation.

Reflectivity and velocity mode on weather radar
Reflectivity and velocity mode on weather radar(KFYR)

However, there are other capabilities of weather radar that can give meteorologists more detailed information about the shapes and sizes of precipitation.

The waveguide that carries the radio frequency energy from the transmitter up to the radar dish is actually split into two inside the radome. Therefore, with the radio frequency energy in two separate waveguides, the radar can send out the energy (which looks like sine waves) in both the horizontal and the vertical orientation. The radar transmits these horizontal and vertical pulses in an alternating manner, which is what’s referred to as dual-polarization radar technology. This allows weather radars to detect the size, shape, and variety of objects in the atmosphere, such as precipitation.

With this technology, we can determine the different types of precipitation that are falling as well as the size and shape of raindrops, hailstones, snowflakes, etc. The radar can also analyze where non-meteorological objects (non-hydrometeors) are, such as bugs and birds, since this gives a different signal back to the radar with the dual-polarization technology.

Dual polarization radar explainer
Dual polarization radar explainer(NWS)

Raindrops and hailstones, for example, come in a variety of different shapes and sizes. Hail can be small, large, smooth, or spiky. Raindrops start off really small within storms, but can grow into much larger “hamburger-shaped” drops, and detecting their size within thunderstorms is very helpful. One application of determining the shape and size of these particles with dual-polarization weather radars is that it can help meteorologists figure out where intensification of thunderstorms and severe weather may happen.

Different shapes and sizes of raindrops and hailstones
Different shapes and sizes of raindrops and hailstones(KFYR)

One of the more important dual-polarization weather radar products is called “differential reflectivity.” This allows meteorologists to compare the vertical scale and horizontal scale of particles in the atmosphere. The example below is from Morton County in 2021 when a supercell thunderstorm was producing baseball size hail to the east of Flasher. In the circled area, there’s a region of differential reflectivity values around zero (the gray shading), indicating the presence of more spherical objects, such as hail. This is in contrast to the higher differential reflectivity values, shown by the yellow and red colors, surrounding the “hail core” of the thunderstorm where large, “hamburger-shaped” raindrops were present.

This dual-polarization radar product really helped meteorologists pinpoint where the large hail was located in this storm. This storm also displayed a “hail spike” on normal reflectivity mode on our radar, which is another indication of very large hail within a storm.

Differential reflectivity explanation and example
Differential reflectivity explanation and example(KFYR/NWS Bismarck)

A second very useful dual-polarization product is called the “correlation coefficient.” This product works by determining how similar or dissimilar particles in the atmosphere are compared to their surroundings. With severe weather, this can serve as a “debris tracker” for detecting where lofted debris from tornadoes is to confirm that a tornado is on the ground and doing damage. Tornadoes can tear apart trees, homes, etc., and lift pieces of them thousands of feet up in the atmosphere. These objects are dissimilar from the surrounding precipitation, such as rain and hail, within the storm, and the correlation coefficient product plots this as a blue area compared to the surrounding yellow and red areas, as shown below on the right side. This example is from 2016 when an EF-2 tornado tracked through parts of Rolette and Towner Counties, and the circled area is where the radar sensed a low correlation coefficient due to lofted tornado debris in that area.

This dual-polarization product helps meteorologists confirm that there is a confirmed tornado on the ground, and the height in the atmosphere that this debris is being lofted can help to determine the intensity of the tornado. Meteorologists call this signature on the correlation coefficient product a tornado debris signature (TDS). In order to verify that there is actually a TDS, we need to match up the correlation coefficient radar data to the normal reflectivity mode information to see if the TDS is in a position within the storm that makes sense. Sometimes, a lowering of the correlation coefficient can be “noise” on the radar, which can be a bit misleading when trying to identify if there is actually lofted debris from a tornado. In this case, the circled area on the reflectivity mode (the left side of the example below) is in a part of the storm where it’s possible that a tornado could form, below a bit of a hook, or curvature, of the higher reflectivity values. These “hook echos” on reflectivity mode can sometimes be more well defined and help to indicate the presence of a tornado.

Correlation coefficient explanation and example
Correlation coefficient explanation and example(KFYR/NWS Bismarck)

In the winter, the correlation coefficient product can also help meteorologists determine where snow is falling versus where rain is falling by highlighting where the melting layer is. This is because the melting layer, where snow and rain meet, is composed of a mixture of different shapes and sizes of particles, and this appears as a low correlation coefficient (as shown in the yellow/light green color below) due to nearby particles being dissimilar within this layer. This is in contrast to the high correlation coefficient of the areas where just rain and just snow are falling (as shown in the red shading below). Determining where the rain/snow line is during winter storms can be vital for snowfall forecasting, as there’s usually a sharp cutoff in snow totals near the melting layer.

Correlation coefficient example in the winter
Correlation coefficient example in the winter(NWS Boston)

This dual-polarization weather radar technology is a fairly recent upgrade to National Weather Service radars.

Chauncy Schultz, science and operations officer at the Bismarck National Weather Service, said: “We added that new dual-polarization technology in 2012. So, it’s relatively recent considering that the radar itself is going on about 30 years old now. The dual-polarization in the last decade or so has really helped us to better detect different kinds of rain and snow, the precipitation types.

And it’s really helped us detect hail a lot better than we did historically because we can tell if it’s small hail, if it’s extra large hail. Now, that really helps us with our warnings. One of the things that we can detect is actually debris. So, thankfully, we haven’t observed that from our radar very often. But if a tornado does damage, the debris field, so all sort of structures and things like that, as it is lofted by a tornado, actually gives a different type of signal as well. The dual-polarization technology lets us parse that out from regular rain and hail in a big damaging supercell thunderstorm, so we can actually detect if a tornado is causing damage from the radar, if it’s close enough to the radar, which we never historically could do before we had dual-polarization.”

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