Cold fronts, Couplets, and Debris Oh My

Radar can be an incredibly useful tool when used in nowcasting or real-time situations.  It has become an indispensable source of data to National Weather Service forecasters as well as researchers.  The events of March 25th across Oklahoma showed how radar can be used to detect several different types of phenomena all occurring within a short time span of one another.

By 2300 UTC March 25th (6 pm local time), storms had erupted along the cold front from west-central Oklahoma into northeastern Oklahoma.  One tornado had already occurred in Sand Springs near Tulsa 30 minutes ealier, unfortunately killing one person. The cold front can be seen in the image below as a thin line of relatively enhanced reflectivity south of several convective storms.


Zooming into the central Oklahoma region, a storm over El Reno is shown just behind the cold front with an associated mesocyclone, a low-level region of rotation within a supercell. The mesocyclone is apparent when examining radial velocity data, with green shading representing wind directions coming towards the radar, and red shading showing where winds are moving away from the radar. Radial velocities are one of six raw data fields that NEXRAD radar provides.  Interpreting radial velocity signatures can be very challenging because you have to account for where the radar data bin is located relative to where the radar is positioned.  The Warning Decision Training Branch has produced a document that provides an in depth discussion on interpreting radial velocity signatures.



The Storm Prediction Center issued a mesoscale discussion concerning storms in central Oklahoma, stating that they would “likely …become quickly undercut by the front.” Indeed, that appeared to be the case as the cold front was already south of the El Reno storm.  Many times when storms are undercut by a cold front or outflow, the storms can , weaken, or pose a reduced threat of tornadic activity.

However, by 2317 UTC, a noticeable kink in the cold front was apparent on radar, showing that the storm, now east of El Reno, was drawing the cold front back to it. By this time, a coworker who was chasing this particular storm saw a partially condensed funnel with a large dust cloud underneath it on the ground a few miles southwest of Yukon.


At 2328 UTC, a noticeable vortex couplet was easily seen in the radial velocity field indicative of a possible tornado.   The couplet shows azimuthally adjacent wind velocities in a direction away from the radar (in red) immediately next to strong wind velocities coming towards the radar (in green).


About 7 minutes later, a new area of rotation rapidly began to develop within the same storm.  However, this new area developed further south, at SE 119th and Pennsyvlania Ave, located along the border between Oklahoma City and Moore.  The local Oklahoma City media were able to capture the unfolding events through video from helicopters.  At 2341 UTC, the tornado had reached I-35 and SE 4th in Moore where it was able to overturn a semi going northbound on I-35.  The enhanced area of reflectivity curled up into a ball is a tornadic debris ball showing an area of lofted debris, not heavy rain.


The same area had extremely low correlation coefficients, well below 0.8.  As noted in a previous blog, correlation coefficient (CC) is a dual-pol parameter that represents how uniform radar scatterers are within a data bin.  Previously, CC had been used in determining the location of the melting layer above the surface.  In this example, CC can also be useful in determining the location of tornadic debris.  Tornadic debris will contain all types of materials of different shapes and sizes, driving the correlation coefficient well below 1.0.


The tornado continued to track southeastward for another 5 minutes, and eventually lifted at SE 34th and Sunnylane in Moore.  Another useful radar product is shown below that can capture the paths of tornadoes referred to as Rotations Tracks.  Rotation Tracks are created by calculating azimuthal shear fields, or the azimuthal derivative of radial velocity. The azimuthal direction is the direction perpendicular to a radar beam, with the radar beam emanating outward in all directions from the radar.  The KTLX radar location is shown by the yellow dot.  The northern-most path shows the primary mesocyclone path for the storm that had tracked from El Reno into southern Oklahoma City.  The second, smaller path further south denotes the path of the Moore tornado.  Rotation Tracks show areas where potential tornadoes may have formed, but a tornado did not necessarily exist across the entire path.  This type of product is useful when used in conjunction with other data to determine the most likely path of a tornado.  However, the Rotation Track product can also be very noisy, showing all types of shear patterns in the atmosphere including gust fronts and cold fronts.


As shown through the events of March 25th, many physical properties and storm attributes can be revealed by radar. However, even an experienced radar meteorologist can be challenged to understand the unfolding events of a severe weather event using radar data.  Interpretation of radial velocities, patterns in reflectivity and uses of dual-pol data can be difficult; especially when trying to interpret what is happening as it is actually occurring in real-time.  However, when several different radar data fields and derived products are used together, especially in hindsight, the progression of severe weather events can be illuminated.

-Chris Porter


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