Understanding Houston's Radar Armadillos Phenomenon

Understanding Houston's Radar Armadillos Phenomenon
Table Of Content

Understanding the Houston Radar Armadillo

The Houston radar armadillo refers to anomalous readings that the National Weather Service occasionally picks up on Doppler weather radars near Houston, Texas. These readings display characteristics similar to armadillos on the radar screen, leading to their nickname of "radar armadillos."

What Causes Radar Armadillos?

The exact cause of radar armadillos is unknown. However, the leading theory is that they are caused by a weather phenomenon known as anomalous propagation. This occurs when atmospheric conditions bend the radar beam, causing it to pick up objects and terrain it would not normally detect.

For example, the radar beam could become ducted and detect the surface of the ground. The movement of ground clutter in the wind could then mimic the appearance of a living creature on the radar display.

Why Are They Called Armadillos?

They earned the "armadillo" nickname because their readings on Doppler weather radar resemble the size and movement of the bony-plated mammals. Armadillos are very common in parts of Texas, including around Houston.

The familiar appearance of armadillos on radar likely led to the coined term that meteorologists and weather enthusiasts now use.

When Radar Armadillos Appear

Houston radar armadillos tend to appear during certain atmospheric conditions, particularly during summer months. Typically, they show up when high pressure causes temperature inversions in the atmosphere.

These inversions act like ducts for the radar signals, trapping them close to the ground and allowing detection of objects the radar beam would usually pass over. This effect generates the armadillo images.

Indicators of Radar Armadillos

Besides the armadillo shapes, radar technicians can identify these false readings through certain characteristics:

  • They tend to move faster than actual animals could.
  • They will disappear and reappear randomly.
  • They do not align with visible storm activity on radar.

Identifying these indicators allows meteorologists to discard the armadillo readings instead of mistaking them for real precipitation or atmospheric features.

Importance for Weather Forecasting

Filtering out radar armadillos improves the reliability of Doppler weather radar. This helps meteorologists make more accurate forecasts and issue better severe weather warnings.

When anomalous propagation generates a lot of ground clutter, it can hide actual storm signatures on radar. Eliminating this clutter provides much clearer data on real rainfall and storm activity.

Ongoing Research

While radar armadillos may sound odd, they provide useful opportunities for research into anomalous propagation. This phenomenon impacts many different types of radar, not just weather radar.

By studying conditions that lead to ducted radar signals, scientists can find ways to better account for and eliminate false returns. This promises to improve radar capabilities across multiple applications.


What exactly are "radar armadillos"?

Radar armadillos refer to strange, armadillo-shaped anomalies that occasionally appear on Doppler weather radar near Houston. They are caused by a phenomenon called anomalous propagation that can produce false radar readings.

Do radar armadillos indicate actual armadillos?

No, radar armadillos are just weather radar artifacts - they do not represent real armadillos or other animals. Their name comes from their resemblance to the familiar mammals on radar displays.

Are radar armadillos unique to Houston?

No, anomalous propagation can cause similar false radar readings showing up as odd shapes and ground clutter elsewhere. But the "armadillo" name originates from radars near armadillo populations in southern Texas.

Why are meteorologists interested in radar armadillos?

Radar armadillos provide opportunities to study the atmospheric conditions that cause anomalous propagation. This will allow improvement of radar technology to filter out clutter and increase forecasting accuracy.

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