101: Weather Radar (Reflectivity)

Radar Reflectivity


Intensity Defined

Reflectivity is the oldest and most widely used product of weather radars. Until the arrival of the WSR-88D in the 1990s, reflectivity was the only base product available for operational use. As mentioned in the previous post, radar power is measured in decibels, a logarithmic unit, because there is such gigantic difference between the power that is emitted by the radar and the power that is returned to the radar. However, one must also consider the fact that since the radar beam spreads out, targets closer to the unit will have stronger returns than those further away, even if the targets' actual intensities are the same. For this reason, a value known as equivalent reflectivity is used to account for difference in power. The equation is actually quite simple:

Equivalent Reflectivity = (power returned to radar * the square of target's range) / (the product of two constants)

Even in this scale, the resulting value can range anywhere from ten to tens of millions, thus another logarithm (base 10) is applied, resulting in units of decibels of equivalent reflectivity (dBZ):

dBZ = 10 * log (equivalent reflectivity)

Thus an equivalent reflectivity value of 10 would yield a dBZ of 10 and a value of a million would yield a dBZ of 60. Negative dBZ values are the result of equivalent reflectivity between 0 and 1. These dBZ values are what is typically used to express reflectivity, thus they are often referred to simply as intensity. Most color tables (figure 1) used in radar images have dBZ values ranging from -10 or 0 to 80 dBZ.

Figure 1: Some of the commonly used color tables used to depict reflectivity intensity.

Level II Base Reflectivity

With the full volume scan that encompasses all tilts, level II reflectivity files allow for the creation of images in three dimensions. The first of these is the radar cross section. These are much like the RHI (range-height indicator) displays of previous radar generations, except the slice can be made through any part of the radar volume, instead of being limited to just along the radials. Cross sections are a great way to identify specific storm structures that might be a sign of severe weather (figure 3). Radar volumes, also known as lit volumes, are 3-D displays of the entire radar scan, regardless of the intensity, depicted as dots (figure 4). By choosing the right color tables and transparency settings, these images allow some of the key structural features of storms to be viewed together. The downside to these displays is that they are often hard to interpret and visualize due to the large amount of data being displayed. Finally, the radar isosurface display limits the amount of data depicted to only the extent of a user defined intensity (figures 5 and 6). Isosurfaces are displayed as smooth surfaces of interpolated data instead of dots, making them clearer, thus they are generally preferred over radar volumes. It is important to remember with all operational radar displays that the radar is not showing the storm cloud itself, but simply the regions in which targets exist to scatter the radar beam (figure 7).

Figure 2: The full resolution level II reflectivity image from the Lubbock, TX radar (KLBB) of the April 11, 2015 (April 12, 2015 0047 UTC) scan used in the following few graphics.

Figure 3: Looking to the southeast, this cross section is oriented east-west and slices through the most intense part of the storm.

Figure 4: The radar volume from same time as above. The dots allow the core of the storm to be seen, although it can be hard to get a clear picture of the storm's structure.

Figure 5: This isosurface is at the same time and marks the extent of the 18.5 dBZ intensity. Notice that it is still a little noisy.

Figure 6: This is also a 18.5 dBZ isosurface, but made using a different program that constructs the surface differently. The flat, sloped top near Lubbock is likely not the top of the storm, but the highest the radar beam was able to reach since the storm was quite close to the radar at the time, so some the the storm was in the cone of silence.

Figure 7: A radar cross section is overlaid onto a screen shot from the Lubbock National Weather Service office's webcam at the same time as the scan. Notice the echo only shows the precipitation core, not the entire cloud's extent. The upper portions of the cross section were made using data from the more distant Amarillo radar (KAMA), which could see into Lubbock's cone of silence.

Level III Products (and their product codes)

Level III Base Reflectivity (N0R, N1R, N2R, N3R, NAR, NBR, and many others)
Many of the derived values produced by the radar's programming uses just the base reflectivity data. The most basic of which are the quality controlled versions of the reflectivity data. Depending on the radar's current VCP, these products can include data from the 0.5 degree tilt up to the 3.5 degree tilt (figure 8). While useful for their small size and quality control, these products are at a lower resolution than their level II counterparts.

Figure 8: The level III base reflectivity of the 0.5, 1.5, 2.5, and 3.5 degree tilts (N0R, N1R, N2R, and N3R, respectively).

Composite Reflectivity (NCO, NCR, NCZ)
After completing the full volume scan, the radar selects the highest value measured for each gate, regardless of tilt, and maps those onto one file (figure 9). This data is useful in locating areas of the strongest intensity, but since it only displays the strongest signal, composite reflectivity typically masks storm structure. Typically it is wise to only use this to identify regions of strong convection when investigating a large region.

Figure 9: The composite reflectivity product (left) compared to the 0.5 degree base reflectivity product. Notice the small red marker on the south side of the storm. On the base reflectivity image it is on the edge of the storm near a large gradient of intensity, while it is well within the composite reflectivity's depiction of the storm. This means there is a part of the upper portion of the storm that must be overhanging the lower levels. A feature such as this is very important and may indicate that the storm is, or will soon be, producing severe weather.

Precipitation (before dual-pol: N1P, N3P, NTP, with dual-pol: OHA, PTA)
These products attempt to estimate the total precipitation that has fallen over the course of the previous hour (N1P/OHA), the previous three hours (N3P), or since the storm began (NTP/PTA). Originally, empirically derived formulas were the basis for converting radar intensity to precipitation amounts. Now that radars have dual-pol capabilities, the radar decides what conversion algorithm to apply to each gate based on what kind of precipitation it estimates to be occurring there. Many assumptions are made that must be taken into account when using these products (figure 10). The most important assumption is that all precipitation the radar detects will reach the ground. In cases of high cloud bases or when a layer of dry air exists below the radar's beam, these products will produce an overestimate because much of the precipitation will evaporate before reaching the surface.

Figure 10: The storm total precipitation from the Seattle, WA radar (KATX) of a widespread heavy rain event displays some of the issues with the precipitation estimate. Notice that the highest values roughly form a ring around the radar. In reality, the rainfall was more or less evenly distributed across most of the region, but at close range the cone of silence prevented much of the precipitation from being counted and at long range the radar beam entirely missed the lower portions of the precipitation.

Vertically Integrated Liquid a.k.a. VIL (NVL, DVL)
This product is used in much the same way as composite reflectivity. Instead of mapping the greatest dBZ value in a column above a point, the VIL product uses an algorithm to estimate the amount of liquid water contained in a column above a point (figure 11). This is useful in locating areas of heavy precipitation and hail.

Figure 11: The VIL product from the same Lubbock storm used earlier shows how the storm's core is highlighted, making it easy to identify the storm as very intense.

Echo Tops (NET, EET)
These images plot the height of the highest return of 18.5 dBZ in a column (figure 12). This is useful for getting a basic grasp of storm structure and is widely used by pilots during briefing. Since the radar beam has limited visibility in the vertical, it may be possible that the height of a 18.5 dBZ intensity may be above the radar's highest tilt, thus the reported echo top would simply be the highest the beam can sample, thus giving limited information about the storm structure. This is particularly a problem close to the radar unit itself where storms can easily extend into the cone of silence.

Figure 12: The echo top product reveals the updraft core of the storm, but the slight curve to the greatest height values (the KLBB radar makes the center of the curve) probably means that the true top of the storm was in the radar's cone of silence.

Storm Structure (NSS) and Storm Track (NST)
By using predefined thresholds, the radar unit attempts to locate the core (called the centroid) of a storm cell. Tracking the location of these cores allows the Storm Cell Identification and Tracking algorithm to estimate properties of storm (figure 13) such as its speed, direction of movement, echo top, VIL, storm base, and maximum reflectivity (as well as the height this occurs at). Some radar visualization programs allow the storm data to be displayed as an overlay on the main image along with lines depicting the forecasted track of the storm over the next hour. If there is uncertainty in the storm motion, the displayed track will be shortened to 45, 30, or 15 minutes. Thus, the length of the track indicates the confidence in the track. It is important to note that the storm motion does not involve any of the other base products, including velocity data.

Figure 13: The storm cell's attributes and forecasted track are overlaid on top of its base reflectivity image.

Hail Index (NHI)
The Hail Detection Algorithm uses a set of criteria to estimate the location of hail. The output is usually displayed either along with the storm structure and track and/or its own overlay icon (figure 14). A key component to the algorithm is the height of the 0 and -20 degree Celsius levels, which are supplied by the radar operator or from the latest forecast model. The output data includes the probability of hail (POH), the probability of significant hail (POSH; 1 in or larger), and the maximum estimated size of the hail stones. Due to the widening of the radar beam at long distances and the issues involving the cone of silence at close ranges, the hail product is considered to be most reliable between 30 and 60 nautical miles (nm) from the radar site.

Figure 14: The green triangle is coincident with the centroid of the cell and indicates the hail size. Further information on the hail can be found in the radar's storm attributes table (the displayed cell is named L0 in the table).