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How Do Hurricanes Get Their Names? (And Other FAQs)

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Many media outlets have dispatched reporters to the Caribbean and Gulf Coast, hoping to get a first-hand account of Hurricanes Gustav, Hanna and Ike. Maybe next hurricane season, Matt Soniak can join them. (We'll start saving.) For now, his contribution to the national weather conversation is this hurricane FAQ.

Let's start small. What is a hurricane?

Tropical cyclones are storm systems that develop in the tropics, characterized by a low pressure center and thunderstorms that produce strong winds, rain and storm surges. "Tropical cyclone" is a generic term that refers to the storms' geographic origin and cyclonic rotation around a central "eye." Depending on their location and strength, the storms are called by other names. When a tropical cyclone occurs in the Atlantic Ocean and has winds with a sustained speed of at least 74 miles per hour, it's called a hurricane. The same storm occurring in the northwestern Pacific Ocean would be called a typhoon.

What's the difference between a hurricane and a tropical storm?

It's a matter of wind speed. Tropical cyclones, when they're just starting out as general areas of low pressure with the potential to strengthen, are called tropical depressions. They're given a sequential number as they form during the storm season.

Once a storm's winds kick up to 39 mph and sustain that speed for 10 minutes, it becomes a tropical storm, and the National Hurricane Center gives it a name (more on this later).

If the storm keeps growing and wind speeds hit 74 mph, we call it a hurricane.

Once we call it a hurricane, how do we categorize it?

We look to the Saffir-Simpson Hurricane Scale, developed as a classification system for tropical cyclones in the Western Hemisphere in 1971 by structural engineer Herbert Saffir and meteorologist Robert Simpson, who was director of the National Hurricane Center (NHC) at the time.

When Saffir was working for the United Nations to study low-cost housing in hurricane-prone areas, it struck him that there was no scale for describing hurricanes and their damaging effects in a simple way, like the Richter scale is used to describe earthquakes. He created a 1"“5 scale based on wind speed and sent it off to the NHC. Simpson expanded Saffir's work to include the effects of storm surge and flooding and began using it at the Center.

If you want to see a breakdown of the scale, head here.

Is there anything worse than a Category 5?

Not on paper, but there have been hurricanes that have gone beyond the upper bounds of the scale. Hurricane Wilma, which hit the U.S. in 2005, was the most intense hurricane ever recorded in the Atlantic, with winds peaking at 175 mph.

Hypothetically, hurricanes could get even worse. The storms use warm water to fuel themselves. As ocean temperatures rise, climatologists predict that potential hurricane intensity will increase. But don't expect the scale to change. Both Saffir and Simpson have said that there's no need to add more categories because once the winds go beyond 156 mph, the damage looks the same: really bad.

How do hurricanes get their Names?

Since Europeans first came to the Americas and the Caribbean, hurricanes were named using a variety of systems. First they were named after Catholic saints. Later on, the latitude-longitude positions of a storm's formation was used as a name. This was a little too cumbersome to use in conversation.

Military meteorologists started giving female names to storms during World War II, and in 1950 the World Meteorological Organization (WMO) adopted the method. The WMO devised a system of rotating, alphabetical names. (Names can be retired at WMO meetings by request from a nation that has been hit by the storm. The name is then not used for 10 years, which makes historic references and insurance claims easier.)

In 1979, the system was given a dose of political correctness: male names were added to the list, as were French and Spanish names, reflecting the languages of the nations affected by hurricanes.

Today, the WMO uses six lists of 21 names (Q, U, X, Y and Z names are not used) that it cycles through every six years, with the gender of the season's first storm alternating year to year, and genders alternating through the rest of the hurricane season. If there are more than 21 named storms in a year, as there were in 2005, the rest of the storms are named for letters in the Greek alphabet.

Occasionally, a storm suffers something of an identity crisis and has its name changed. This happens when a storm crosses from one ocean to another, or if it dies down and then redevelops.

Will my name be a hurricane this year?

If your name is Nana, then yes. The names being used for the 2008 season are Arthur, Bertha, Cristobal, Dolly, Edouard, Fay, Gustav, Hanna, Ike, Josephine, Kyle, Laura, Marco, Nana, Omar, Paloma, Rene, Sally, Teddy, Vicky and Wilfred.

See also...

Why can't you pump your own gas in Oregon and New Jersey?
*
Why do we sing the national anthem at sporting events?
*
Why do we yawn?

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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iStock
Animals
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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