GWCC Weather Radar Education
Radar History
Who invented the first radar technology and when?
Radar technology had its origins in classical experiments on electromagnetic radiation conducted by German physicist Heinrich Hertz during the late 1880’s. It wasn’t until 1935, by way of Sir Robert Alexander Watson-Watt, that the first radar system was invented. Watson-Watt took Hertz’s ideas and built them into a physical reality with his own early-on radar system design.
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Heinrich Hertz
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Sir Robert Alexander Watson-Watt
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When was the first Doppler radar invented?
In 1842, an Austrian physicist by the name of Christian Andreas Doppler described how the frequency of light and sound waves were affected by the relative motion of an object. This phenomenon became known as the Doppler effect. The Doppler effect is effectively a phase shift change in frequency or wavelength which is caused by the distance between the object being observed and the observer. A positive phase shift implies forward motion toward the radar and a negative shift suggests retreating motion away from the radar. The phase shift effect is similar to the "Doppler shift" which can be observed under many circumstances with sound waves movement/propagation. If an object emits sound waves as it approaches a location, the waves are compressed and consequently will then lead to a higher frequency being observed. As the object moves away from a given location, the sound waves are then stretched, leading to a lower frequency. This is often experienced when an emergency vehicle drives past with its siren blaring or within the context of hearing an approaching train reaching a station platform.
In 1842, an Austrian physicist by the name of Christian Andreas Doppler described how the frequency of light and sound waves were affected by the relative motion of an object. This phenomenon became known as the Doppler effect. The Doppler effect is effectively a phase shift change in frequency or wavelength which is caused by the distance between the object being observed and the observer. A positive phase shift implies forward motion toward the radar and a negative shift suggests retreating motion away from the radar. The phase shift effect is similar to the "Doppler shift" which can be observed under many circumstances with sound waves movement/propagation. If an object emits sound waves as it approaches a location, the waves are compressed and consequently will then lead to a higher frequency being observed. As the object moves away from a given location, the sound waves are then stretched, leading to a lower frequency. This is often experienced when an emergency vehicle drives past with its siren blaring or within the context of hearing an approaching train reaching a station platform.
Christian Andreas Doppler
Why was the invention of the earliest Doppler radar technology such a BIG deal?
The first Doppler radar technology revolutionized weather forecasting in ways that were never before thought possible. First off, the onset of the earliest Doppler radar technologies provided completely new ways to forecast and view weather systems along with improving forecasts. Doppler radar revolutionized the weather forecasting industry, providing new intel and data from observed storms. More specifically, the introduction of even the earliest Doppler radar technologies provided increasingly more state-of-the-art insights into storm structure as well as storm dynamics during all seasons of the year. Effectively, meteorologists learned about weather ten-fold, once Doppler radar was introduced.
The first Doppler radar technology revolutionized weather forecasting in ways that were never before thought possible. First off, the onset of the earliest Doppler radar technologies provided completely new ways to forecast and view weather systems along with improving forecasts. Doppler radar revolutionized the weather forecasting industry, providing new intel and data from observed storms. More specifically, the introduction of even the earliest Doppler radar technologies provided increasingly more state-of-the-art insights into storm structure as well as storm dynamics during all seasons of the year. Effectively, meteorologists learned about weather ten-fold, once Doppler radar was introduced.
How have weather radar technologies evolved since their earliest beginnings?
Radar started out being used heavily by the military to identify potential enemy targets from far distances. Once it’s capability was noticed, scientists utilized radar to identify weather phenomena such as rain, snow, and hail. In addition to standardized measurements of various atmospheric hydrometeors, mathematically-derived radar products now facilitate a more detailed picture and in-depth analyses of in-storm and in-cloud dynamics for atmospheric events occurring within the observable range of a given radar site. Most radars in use currently across the contiguous United States were first installed in the early 1990s and were collectively completed around the Summer of 2013.
Credit: Andrew J Oldaker
The Workings of A Weather Radar
How does a Doppler radar work?
Doppler radar systems provide information regarding the movement of targets as well as their position with time. A radar unit consists of a transmitter and a receiver. The transmitter sends out pulses of radio waves. The radar transmits pulses of radio waves and keeps track of the phase (i.e., shape, position, and form) of the pulses being sent away from the radar site. By measuring the shift, or change in phase between a transmitted pulse, the target’s movement directly toward or away from the radar is calculated. Precipitation scatters these waves, sending back some energy to the transmitter. When the energy is sent back, it is detected by the radar’s receiver. The intensity of this received signal, called the radar echo, indicates the intensity of the precipitation being observed at a specific time. Measuring the time it takes for the radio wave to leave the radar and return can tell us how distant the storm is from a given location. The direction the radar is pointing then helps to locate both the position and relative distance of a given storm.
Credit: National Weather Service
What are Volume Coverage Patterns (VCP)?
“When it comes to understanding how a Doppler radar works, a radar continuously scans the atmosphere by completing volume coverage patterns (VCP). A VCP consists of the radar making multiple 360° scans of the atmosphere, sampling a set of increasing elevation angles.
There are two main operating states of the Doppler radar; Clear Air Mode and Precipitation Mode. Clear Air mode is used when there is no rain within the range of the radar. In this mode, the radar is in its most sensitive operational state. When precipitation is occurring, the radar does not need to be as sensitive as in clear air mode as rain provides plenty of returning signals. At the same time, meteorologists want to see higher up in the atmosphere when precipitation is occurring to analyze the vertical structure of any storms. This is when the meteorologists switch the radar to precipitation mode. Within these two operating states there are several VCPs the NWS forecasters can utilize to help analyze the atmosphere around the radar. These different VCPs have varying numbers of elevation tilts and rotation speeds of the radar itself. Each VCP therefore can provide a different perspective of the atmosphere.
“When it comes to understanding how a Doppler radar works, a radar continuously scans the atmosphere by completing volume coverage patterns (VCP). A VCP consists of the radar making multiple 360° scans of the atmosphere, sampling a set of increasing elevation angles.
There are two main operating states of the Doppler radar; Clear Air Mode and Precipitation Mode. Clear Air mode is used when there is no rain within the range of the radar. In this mode, the radar is in its most sensitive operational state. When precipitation is occurring, the radar does not need to be as sensitive as in clear air mode as rain provides plenty of returning signals. At the same time, meteorologists want to see higher up in the atmosphere when precipitation is occurring to analyze the vertical structure of any storms. This is when the meteorologists switch the radar to precipitation mode. Within these two operating states there are several VCPs the NWS forecasters can utilize to help analyze the atmosphere around the radar. These different VCPs have varying numbers of elevation tilts and rotation speeds of the radar itself. Each VCP therefore can provide a different perspective of the atmosphere.
Credit: National Weather Service, NOAA
The scanning begins with 0.5° elevation meaning the centerline of the radar beam antenna is angled 0.5° above the ground. Since the beam itself is 1° wide, it returns information about what it "sees" between 0° and 1° above the horizon.
After it completes all 360° sweeps at the 0.5° angle of elevation, the radar is tilted to the next elevation angle in that particular VCP. This process repeats until all elevation angles have been completed after which the Doppler radar processes the received information and produces the radar images you commonly see.” (Credit: National Weather Service, NOAA)
After it completes all 360° sweeps at the 0.5° angle of elevation, the radar is tilted to the next elevation angle in that particular VCP. This process repeats until all elevation angles have been completed after which the Doppler radar processes the received information and produces the radar images you commonly see.” (Credit: National Weather Service, NOAA)
What is dual-polarization and how does it work? And, why is dual-polarization radar technology so important in an operational context?
Doppler radars were upgraded to Dual-polarized radar technology because the earlier WSR-88D style radar technology in operations at the time was becoming outdated. Dual-polarization revolutionized radar technology by providing better resolution and a clearer view of storms and corresponding storm structure which is critical for real-time forecasting and research purposes. Dual-polarized radars send both horizontal and vertical electromagnetic waves to examine a variety of particle, hydrometeor, and/or biological target types existing within different types of air masses. These perpendicular fields bounce off of an object and return back to the radar which then gives information on the horizontal and vertical dimensions of particles, hydrometeors, and/or biological targets within the observable range of a given radar site. Dual-polarized radar technology is important because it can accurately predict the amount of potential rainfall. Also, it can differentiate between heavy rain and hail, which can improve the efficiency and accuracy of flash flood watch and/or warning issuance. This technology can also improve winter weather forecasts as a result of its ability to help improve snowstorm and ice storm forecasts.
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Standard WSR-88D Doppler Radar
Credit: National Weather Service
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Dual-Pol WSR-88D Doppler Radar
Credit: National Weather Service
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What are the different data products produced by a dual-polarized weather radar system and what do they tell us about the state of a given part of the atmosphere?
Three of the main data products that dual-polarized radar produces are Correlation Coefficient, Differential Reflectivity, and Differential Phase Shift.
Differential Reflectivity is a ratio of the horizontally polarized reflectivity to the vertically polarized reflectivity. Differential Reflectivity (ZDR) can be used to help identify hail shafts, updrafts, determine the size and the aggregation of dry snow. Differential Reflectivity is best defined as the difference between the horizontal and vertical reflectivity values which are observed in terms of dBZ units.
Credit: NOAA
More specifically, “Differential Reflectivity values are biased toward larger particles. Stated differently, the larger the particle, the more it contributes to the resulting reflectivity factor. Hence while raindrops usually are wider than they are tall which would tend to yield a positive ZDR value, a scattering of large hailstones in the same volume of air being observed will yield a ZDR value closer to 0, because the spherical shape of the larger objects contributes more to the final reflectivity value. If the base reflectivity product is indicating high dBZ values whereas differential reflectivity is returning values near zero, then the volume in question is likely filled with a mixture of hail and rain.” (Credit: Radarscope)
Correlation Coefficient (CC) provides a measure of the consistency of the shapes and sizes of targets within the radar beam. CC helps to identify the melting layer in a storm, hail, tornadic debris along with distinguishing meteorological vs non-meteorological targets. More specifically, CC is defined as being the measure of how similarly the horizontally and vertically-oriented polarized pulses are behaving upon being emitted from a radar site and interacting with various objects in the path of the given pulses. Its values range from 0 to 1 and are unitless, with higher values indicating similar atmospheric interactive behavior and lower values conveying more variable behavior.
Credit: NOAA
CC is particularly effective and useful for differentiating between variable echoes of meteorological significance. “Non-meteorological echoes (such as birds, insects, and ground clutter) produce a complex scattering pattern which causes the horizontal and vertical pulses of the radar to vary widely from pulse to pulse, yielding CC values typically below 0.8. Hail and melting snow are non-uniform in shape and thus cause a scattering effect as well, but these meteorological echoes will tend to more often exhibit more moderate CC values ranging from 0.8 to 0.97. Uniform meteorological echoes such as those found in association with rain and hail yield well-behaved scatter patterns, and their CC from pulse to pulse generally exceeds 0.97.” (Credit: Radarscope)
Differential Phase Shift is a measure of the difference in two-way attenuation. Two-way attenuation is effectively the interruption or disruption (or slowing down) in the efficiency of the outgoing and/or incoming radio wave signals from a given radar site for the horizontal and vertical pulses in a given radar scan. It's derived product, Specific Differential Phase (KDP) shows the gradient, or change in Differential Phase Shift. Increasing KDP is an indication of an increase in size and concentration of raindrops and rain rate. Differential phase shift (technically classified as propagation differential phase shift) is “the difference between the horizontal and vertical pulses of the radar as they propagate through a medium such as rain or hail and are subsequently attenuated.” (Credit: Radarscope)
Credit: NOAA
“Differential Reflectivity (ZDR), there is a crucial distinction: differential phase is dependent on particle concentration. That is, the more horizontally-oriented targets are present within a pulse volume, the greater the positive differential phase shift. Thus, a high frequency of small raindrops could yield a higher differential phase value than a lower concentration of larger raindrops. Differential phase shifting is mostly unaffected by the presence of hail, and shifts in snow and ice crystals are typically near zero degrees. Non-meteorological echoes (birds, insects, and so forth) produce highly variable differential phase shifts.” In addition, “Hail and snow/ice crystals typically have no preferred orientation and will yield KDP values near zero degrees. Non-meteorological echoes will often result in noisy KDP values being realized. KDP is not calculated for areas in which the Correlation Coefficient (CC) is less than 0.9, which can often result in unexpected derived radar product data gaps.” (Credit: Radarscope)
How are Doppler radars specifically used to study and track tornado development?
A Doppler radar can detect wind speed, wind direction, and rotation (the last critical component of those three being a factor which can sometimes be a leading indicator of potential tornadic development). There are specific radar signatures which help to indicate tornadic development. Some of these radar signatures include (but are not limited to) hook echoes, rapid wind velocity and/or directional changes over a short distance, and a debris ball signature which indicates the presence of a tornado on the ground. With certain radar products as noted in the point above, tornado signatures are very pronounced which helps forecasters decide if there is a tornado on the ground. Rotational signatures are often quite visible on radar and let forecasters actually see if there is in fact rotation within a given tornadic storm.
Radial Velocity (left) and Base Reflectivity (right) from the 28 May 2013 Bennington, Kansas tornado. Credit: National Weather Serivce
How are Doppler radar systems used to help forecast as well as study the evolution of winter weather events?
Doppler radar systems are used in weather forecasting to measure the direction and speed, or velocity, of objects such as drops of precipitation. These radar systems can also detect the movement of weather systems across vast distances as well as if the system is moving toward or away from the radar. More specifically, in winter weather events, specific radar products (such as correlation coefficient) can greatly help forecasters to distinguish whether a given region of precipitation reaching the ground happens to be of a frozen, liquid, and/or mixed precipitation mode. Such radar products are often also used in a real-time context to establish how quickly and to what extent precipitation type may be changing during a given winter weather event as a result of variable changes with respect to low to mid-level cold air and/or warm air intrusions. In addition, various Doppler radar products can also be quite helpful for identifying much smaller-scale (or mesoscale) changes in snow band evolution during the course of a given winter storm. This includes (but is not limited to) snow band coverage extent and intensity as well as the rate of forward or backward movement of a given snow band relative to a given location of concern.
Animated Radar Imagery Examples
Sea-breeze
Credit: Weather Underground
Sea breeze front moving ashore along the New Jersey and Delaware coastline back on the afternoon of June 20th, 2000. You can identify the sea-breeze front based on the enhanced Doppler reflectivity values (i.e., the approximately red-colored line) just inland from the immediate coastal regions and moving further inland with time.
Light Rain
Credit: National Weather Service, NOAA
Here we can see an elongated precipitation field stretching from central/northern Michigan and stretching down through the central Ohio and Tennessee Valleys back on January 8th, 2018. It is worth noting that the northern extent of this precipitation field began as freezing rain/light sleet; whereas the southern extent of this precipitation region was predominantly composed of rainfall during the majority of this event.
Heavy Rain
Credit: UCAR
Heavier rainfall occurring in association with multiple pulses of energy moving through the lower to middle levels of the atmosphere across Oklahoma and Texas on June 13th, 2016. You can see how during the course of this heavy rainfall event across this region, the deeper convection occurred in multiple convective modes. These storms were slow-moving, especially in Oklahoma, and frequently went through dissipating and re-development stages. In addition, across certain regions, you can see how there were some instances in which heavier rainfall occurred more than once over the same area which is an atmospheric phenomenon referred to as convective training.
Squall Line
Credit: National Weather Service, NOAA
A line of strong to severe thunderstorms (also known as a squall line) which occurred in association with an approaching cold front which was tied to a strong low-pressure system positioned much farther north on April 5th, 2011. You can also see that as the squall line continued to progress further east with time, there was a weaker linear band of light to moderate precipitation following the passage of the deeper convection which is referred to as the trailing stratiform (i.e., lighter) precipitation region.
Derecho
Credit: National Weather Service, NOAA
A line of bowing deep convection (also known as a derecho) progressing across the interior region of New York state back on September 7th, 1998. You can see how as the deeper convection continued to progress across New York (i.e., approximately from the eastern half of Lake Ontario to roughly the capital district of Albany) the deepest convection continued bowing out with time which helped to generate the environmental conditions favorable for strong, damaging winds associated with a severe (bowing) thunderstorm known as a derecho, as noted above. This was an incredibly destructive severe weather event which caught many people in its path by complete surprise with it occurring during the overnight hours.
Quasi-linear Convective System
Credit: National Weather Service, NOAA
An example of a quasi-linear convective system (QLCS) which unfolded on the evening of March 19th, 2012 across northern Texas. You can see how the quasi-linear line of convective storms (or QLCS) developed with time as more and more notches formed within the line of thunderstorms which facilitated the development of the atmospheric phenomenon referred to above as a quasi-linear convective system. QLCS events can bring heavy rainfall, strong winds, lightning, and even the occasional threat of tornadoes under certain circumstances.
Single-Vortex Tornado
Credit: National Weather Service, NOAA
On both May 19th and May 20th, 2013, National Severe Storms Laboratory (NSSL) researchers collected data on storms that produced tornadoes using both the National Weather Radar Testbed (NWRT) Phased Array Radar (PAR), and the mobile dual-polarized radar. The NWRT PAR can scan the sky in less than one minute (i.e., five-times faster than current operational weather radars). Datasets from the rapidly-updating NWRT PAR will help researchers better understand the evolution of rotating thunderstorms and the tornadoes they produce. The NWRT PAR scanned the Newcastle-Moore tornadic storm for almost an hour. However, the radar imagery for this storm shown above is courtesy of the Oklahoma City, Oklahoma radar site. In this particular storm, the majority of the tornado’s lifetime involved a singular vortex which means that there are no additional “satellite vortices” surrounding the main tornado. Meaning, there is only a single vortex associated with the evolving tornado.
Multi-Vortex Tornado
Credit: National Weather Service, NOAA
The largest tornado in recorded history as shown above occurred on May 31th, 2013 and this was an EF-5 tornado which impacted the city of El Reno, Oklahoma. The EF-5 re-classification was based upon Doppler radar data taken by Oklahoma University's mobile RaXPol radar. According to comments made by tornado researcher Rick Smith, the mobile radar was positioned on top of an overpass and recorded winds close to the surface of up to 295 mph in satellite suction vortices that orbited the large, main vortex. The large, main vortex had EF-4 winds of 185 mph, and the satellite suction vortices moved across the fields at that speed, and rotated on their own at speeds of up to 110 mph, giving a combined wind speed of up to 295 mph in some of the satellite vortices. Thus, with the satellite vortices surrounding the main vortex, this makes this tornado a multi-vortex tornado as compared to a single-vortex tornado.
Dissipating Tornado
Credit: National Weather Service, NOAA
A brief tornado touchdown occurred on May 9th, 2016 as shown above, courtesy of the Oklahoma City, Oklahoma radar site. You can see how the tornado formed right around the city of Davis, Oklahoma before dissipating shortly thereafter around the city of Sulphur, Oklahoma. This is verified by the formation of the marquee tornado signature feature known as a hook echo which formed and then quickly dissipated right around those respective Oklahoma cities. From that point forward, the previously tornadic storm weakened rather quickly as it passed the city of Hickory, Oklahoma.
Hail Core
Credit: National Weather Service, NOAA
Here is an example of a substantial hail event which occurred back on June 5th, 2019. During this event, a few localized weather features came together came together across eastern Wisconsin (i.e. a lake breeze and a surface trough of low pressure) to help initiate strong to severe thunderstorm development. One of the storms that formed ended up producing hailstones whose size were close to tennis balls. The radar imagery shows the purple shades (near 70 dBZ, or 100 times as much return as 50 dBZ that as is the lower edge of red on radar in its logarithmic pattern.) In addition, a three-body scatter spike (as noted above) is an artifact on a weather radar display which is an indication of large hail being present. They are identified by a spike of weak reflectivity echoes that extend out from a thunderstorm which can be seen above.
Essentially, hail spikes are the result of energy from the radar hitting hail, or very heavy rain, and being reflected to the ground, where they reflect back to the hail and then, again, back to the radar. This results in the radar picking up the energy from the multiple path at a later time than the energy that came back directly from the hail to the radar. Both are however on the same radial angle from the radar as the antenna often does not have the time to turn enough.
Virga
Credit: Weather Underground
An example of virga occurring as snowfall advancing towards Long Island and the New York City metro area was not reaching the ground as the winter storm approached back on January 7th, 2019. Later in the day, snowfall did end up reaching the ground as the atmosphere became sufficiently saturated close to and right at the surface that snowfall could reach the ground without evaporating. You can identify the regions in which virga was occurring by way of the lighter blue-colored precipitation regions, indicating lighter snowfall which was not reaching the ground for over an hour in some cases despite the Upton, New York radar site showing lighter snowfall over the region for close to or even over an hour in some cases.
Snowstorm
Credit: The Weather Company
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Credit: National Weather Service, NOAA
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Here is an example of a major snowstorm which impacted the Interstate-95 corridor from approximately Philadelphia, Pennsylvania to Augusta, Maine. You will note how as the winter storm evolved, there was increasingly more dense pink-colored hues moving towards northern New Jersey, Long Island, and Connecticut which indicated the northward progression of the “freezing line” (i.e., the dividing line) between the rain (green-colored) and snow-dominated (blue-colored) regions of the storm. It is also worth noting that the pink-colored regions are typically composed of sleet and other mixed precipitation.
Landfalling Tropical Storm
A view of Tropical Storm Franklin from August 8th, 2017 as the circulation of Franklin was quickly approaching the eastern coastline of Belize. Note how, despite the relatively disorganized nature of Franklin, there was still substantial cyclonic rotation found in association with Franklin. This is quite common for tropical storms since there is still a core low-level, low-pressure circulation tied to the tropical storm which facilitates spiral bands as shown above.
Landfalling Hurricane
Credit: National Weather Service, NOAA
A short-range view of Hurricane Hermine approaching and making landfall in the vicinity of Tampa Bay, Florida. Note how as the system makes its final approach towards the greater Tampa Bay area, you can see the increasingly clearer structure tied to the spiral rainbands. However, as the system moves ashore into portions of northern Florida, you can also see how the symmetry of the hurricane quickly degrades with time which is a result of the hurricane not being able to extract energy from the warm waters of the Gulf of Mexico once the center of Hermine’s circulation moved ashore.
Landfalling Major Hurricane
Credit: National Weather Service, NOAA
A short-range view of the approach and then landfall of Category 5 Hurricane Michael in the vicinity of Mexico Beach, Florida along the Florida Panhandle on October 10th, 2018. Note how you can see robust and symmetric storm structure maintained both during and well after the point of landfall. This was a direct result of the fact that this particular storm continued to intensify right up to the point of landfall and then it takes time for a major hurricane of such a high intensity to begin to wind down as it moves further inland with time. You can also make out the truly classic eyewall convection along with the typical spiral rain band structure.
Outflow Boundaries (emerging from convective storms)
Credit: National Weather Service, NOAA
This is a classic example of an outflow boundary racing away from convective storms which developed and raced across parts of southeastern New England (including the states of Massachusetts, Rhode Island, New Hampshire, and Connecticut) on July 23rd, 2016. You can identify the position of the outflow boundary by the southward-moving elongated blue line racing towards Interstate-95 and the Long Island Sound. Such outflow boundaries are often realized as the onset of much cooler air and breezy conditions (i.e., during the Summer-time such as this event which occurred in late July 2016).
Outflow boundaries (generating convective storms)
Credit: NEXLAB - College of DuPage
This is a great, labelled example for how outflow boundaries from previous convective storms occurring in and around Peachtree City as well as Atlanta, Georgia on August 11th, 2013 collided and consequently generated new convective storms. This re-invigoration of convection in association with the collision of convective outflow boundaries occurs as a result of cooler air at the surface moving away from a given storm and then lifting warmer air out ahead of it. When two opposing outflow boundaries collide, this invigorates convective storm development as a result of two areas of lifted/destabilized warm air coming together and developing into a convective storm.
Biological Targets (Butterflies, bats, birds, etc.)
Movement of Mayflies
Credit: National Weather Service, NOAA
On the evening of July 20th, 2014, the Mississippi River produced a massive radar echo which was generated as a result of mayflies emerging from the water and becoming airborne. The mayflies were detectable on radar by around 8:45 PM CDT and reports in the towns and cities began rolling in of the swarming and piles of mayflies.
The radar detected the flies at about 8:45 PM CDT, emanating from the river (the source) with echo values similar to that of light-moderate rain (35-40 dBZ). With a general south-to-north wind flow above the surface, the mayflies quickly moved north once in the air as reflected by the path of plume burst shown above. As the flies dispersed moving north-northeast, they also gained altitude with some of the plume’s echo being detected as far north as Black River Falls and as high as 2500 feet above the ground. The radar loop below shows the reflected radar energy (reflectivity) from 8:35 PM CDT to just after midnight. The higher the values (greens to yellows) indicate greater concentrations of flies. Note how the swarm is carried northward over time.
Movement of Purple Martins
Credit: BirdCast
A view of Purple Martins leaving their roosts for a day of hunting during the early-morning hours of August 4th, 2017. You will note how when these birds leave their roosts that the local radar site recognizes this exodus of birds as an outward circular burst of reflectivity returns in association with the emergence of birds from their roosts.