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CycloneCenter @ the AMS Tropical Meteorology Conference

CycloneCenter Principal investigator Dr. Chris Hennon of UNC-A presented some recent results at the American Meteorological Society Conference on Hurricanes and Tropical Meteorology going on this week in San Diego, CA.

Cyclone Center at AMS Tropical 2014

Featured Storm – Hurricane Cindy (2005)

Every hurricane season begins with an “A” storm and then moves through the alphabet. Even though the Atlantic Hurricane season is only a few weeks old, we’ve already seen Tropical Storms Andrea and Barry.

Cyclone Center is reliving the 2005 Hurricane Season. We started with Arlene and Bret, and now we’re working Cindy. Eventually we’ll get to some infamous storms like Katrina, Rita, and Wilma before we wrap up with Zeta.

We didn’t pick these storms to bring back memories of these terrible disasters. They actually play a key role in our project. The Atlantic is the only part of the world with routine aircraft reconnaissance. Hurricane Hunters from the U.S. Air Force and NOAA fly specially designed airplanes into these storms to find their centers and measure their strengths. We’ll be using their observations to calibrate the data we collect from your classifications. 2005 was a record-breaking year with 31 tropical storms, so we have a wealth of data!

Courtesy of the National Hurricane Center.

Courtesy of the National Hurricane Center.

Hurricane Cindy formed in the western Caribbean and moved northward across the Yucatan and the Gulf of Mexico on its way to Louisiana. Forecasters classified it as a tropical storm at the time, but it was later upgraded to a hurricane in the “best track” data. Cindy passed just to the east of New Orleans, causing minor flooding and widespread power outages. Little did anyone know that it was just a trial run for Katrina eight weeks later.

Hurricanes sometimes spawn tornadoes as the move inland. Cindy was associated with 33 tornadoes across the Southeastern United States. The strongest of these, and F2 on the Fajita scale, damaged the Atlanta Motor Speedway.

Courtesy of the National Weather Service, Peachtree, GA.

Courtesy of the National Weather Service, Peachtree, GA.

Log on to Cyclone Center today and classify Cindy.

Is it an Eye?

Identifying eye hurricanes is a main focus for the Cyclone Center team, but it is presenting some challenges for our citizen scientists.  Storms with real eyes are being categorized very well, with 80% to 90% accuracy in storm type.  However, storms that do not have eyes but look like they might are proving more difficult.  Many things, like blurry images or dark blue or white clouded centers have been shown to cause these mistakes.

A bizarre example of an image on Cyclone Center that is very misleading is the storm CYC1981.  The small white circle in the very center of the storm that at first glance looks like an eye is actually the island Niue in the South Pacific.  The satellite image was taken as the hurricane passed over the island, and the white land boundary lines look like the eyewall.

1981047S18181.CYC1981.1981.02.17.0900.47.GOE-3.030.hursat-b1.v05

CYC1981

Unfortunately, with the size of the images on Cyclone Center, it is hard to determine if this storm has an eye, and since having an island in the middle of a storm image is a rare phenomenon, it would be easy to assume that it did.  This image of CYC1981 even stumped most of our science team, so don’t feel bad if it tricked you too.

So how can we tell if a storm is or is not an eye storm?

Many storms look very similar in size and shape to eye hurricanes, but they lack an actual eye.  There are a few things that you can look for, however, to determine for sure whether or not the image you are looking at is an image of an eye storm.

  1. Is the center of the storm surrounding the eye cold?  You can tell this by the color of the clouds—shades of red, orange, and grey signify warm clouds while blue and white areas represent cold clouds.
  2. Is the eye itself warm?  The eye should be made up of warm clouds, usually grey or pink colored.  White and grey clouds are not one and the same; white clouds are very cold and grey clouds are very warm.

If we applied these three steps to CYC1981, we would find that it does have cold clouds at the center, but there are no warm clouds around where the eye should be and the band of clouds around the storm is very weak.

For more information, visit another recent post: How do I classify this? False eyes.

This post was contributed by Brady Blackburn, an intern with the Cyclone Center team from Asheville High School in Asheville, NC.

Introduction to Cyclone Center Images

The images you see on Cyclone Center were observed by infrared sensors on weather satellites. These sensors provide an estimate of the temperature at the tops of clouds. Cloud top temperatures are very important because they give us an idea of how tall the clouds are. Temperature decreases with height in the lower atmosphere (up to 10 miles), so cold clouds are taller than warm clouds. Taller clouds are responsible for the heavy rain and thunderstorms that drive tropical cyclones.

In the Cyclone Center images, the cloud top temperatures are represented by a range of colors. The scale on the image above shows the temperatures in degrees Celsius that correspond with each color.

Black and gray are the warmest, indicating temperatures from 9°C (48°F) to 30°C (86°F). Often these will be the temperatures we experience at the land or ocean surface, but they can also be associated with very low clouds. Shades of pink go down to -30°C (-22°F). In our images, these are almost always associated with low clouds. Red, orange, and yellow come next, and they indicate medium-level clouds.

In most images, the coldest clouds you see will be shades of blue. Sometimes you’ll even see a cloud that’s so cold it shows up as white. These clouds are colder than -85°C (-121°F). Coastlines and political borders are also drawn in white, so make sure the white clouds are surrounded by dark blue. Otherwise, you might just be looking at a small island.

Sometimes there is a problem with parts of the satellite data. These missing data will show up as black lines in the images. Just ignore them and carry on with the analysis when you see them.

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