Researchers devise more accurate method for predicting hurricane activity

Sep 11, 2012
Researchers from North Carolina State University, including Dr. Fredrick Semazzi (pictured), have developed a new method for forecasting seasonal hurricane activity that is 15 percent more accurate than previous techniques. Credit: Roger W. Winstead, North Carolina State University

Researchers from North Carolina State University have developed a new method for forecasting seasonal hurricane activity that is 15 percent more accurate than previous techniques.

"This approach should give policymakers more reliable information than current state-of-the-art methods," says Dr. Nagiza Samatova, an associate professor of at NC State and co-author of a paper describing the work. "This will hopefully give them more confidence in planning for the ."

Conventional models used to predict seasonal rely on classical statistical methods using historical data. Hurricane predictions are challenging, in part, because there are an enormous number of variables in play – such as temperature and humidity – which need to be entered for different places and different times. This means there are hundreds of thousands of factors to be considered.

The trick is in determining which variables at which times in which places are most significant. This challenge is exacerbated by the fact that we only have approximately 60 years of historical data to plug into the models.

But now researchers have developed a "network motif-based model" that evaluates historical data for all of the variables in all of the places at all of the times in order to identify those combinations of factors that are most predictive of seasonal hurricane activity. For example, some combinations of factors may correlate only to low activity, while other may correlate only to high activity.

The groups of important factors identified by the network motif-based model are then plugged into a program to create an ensemble of statistical models that present the hurricane activity for the forthcoming season on a scale. For example, it might say there is an 80 percent probability of high activity, a 15 percent probability of normal activity and a 5 percent probability of low activity.

Definitions of these activity levels vary from region to region. In the North Atlantic, which covers the east coast of the United States, high activity is defined as eight or more hurricanes during hurricane season, while normal activity is defined as five to seven hurricanes, and low activity is four or fewer.

Using cross validation – plugging in partial historical data and comparing the new method's results to subsequent historical events – the researchers found the new method has an 80 percent accuracy rate of predicting the level of hurricane activity. This compares to a 65 percent accuracy rate for traditional predictive methods.

In addition, using the network model, researchers have not only confirmed previously identified predictive groups of factors, but identified a number of new predictive groups.

The researchers plan to use the newly identified groups of relevant factors to advance our understanding of the mechanisms that influence hurricane variability and behavior. This could ultimately improve our ability to predict the track of hurricanes, their severity and how global climate change may affect hurricane activity well into the future.

Explore further: Clean air: Fewer sources for self-cleaning

More information: The paper, "Discovery of extreme events-related communities in contrasting groups of physical system networks," was published online Sept. 4 in the journal Data Mining and Knowledge Discovery.

add to favorites email to friend print save as pdf

Related Stories

El Nino may calm 2006 hurricane season

Sep 07, 2006

Hurricane forecasters say a weather phenomenon called El Nino may make the rest of the 2006 Atlantic hurricane season quieter than predicted.

It's relative: Contrasting hurricane theories heat up

Oct 31, 2008

In a paper published in the journal Science today, scientists Gabriel A. Vecchi of NOAA's Geophysical Fluid Dynamics Laboratory, Kyle L. Swanson of the University of Wisconsin - Milwaukee Atmospheric Scienc ...

Researchers foresee relatively quiet hurricane season

Apr 11, 2012

(Phys.org) -- Researchers at North Carolina State University aren’t looking for any surprises with the 2012 hurricane season – they believe that storm activity in the Atlantic basin will be in line ...

Recommended for you

Clean air: Fewer sources for self-cleaning

7 hours ago

Up to now, HONO, also known as nitrous acid, was considered one of the most important sources of hydroxyl radicals (OH), which are regarded as the detergent of the atmosphere, allowing the air to clean itself. ...

There's something ancient in the icebox

7 hours ago

Glaciers are commonly thought to work like a belt sander. As they move over the land they scrape off everything—vegetation, soil, and even the top layer of bedrock. So scientists were greatly surprised ...

Image: Grand Canyon geology lessons on view

14 hours ago

The Grand Canyon in northern Arizona is a favorite for astronauts shooting photos from the International Space Station, as well as one of the best-known tourist attractions in the world. The steep walls of ...

First radar vision for Copernicus

14 hours ago

Launched on 3 April, ESA's Sentinel-1A satellite has already delivered its first radar images of Earth. They offer a tantalising glimpse of the kind of operational imagery that this new mission will provide ...

User comments : 0

More news stories

There's something ancient in the icebox

Glaciers are commonly thought to work like a belt sander. As they move over the land they scrape off everything—vegetation, soil, and even the top layer of bedrock. So scientists were greatly surprised ...

Clean air: Fewer sources for self-cleaning

Up to now, HONO, also known as nitrous acid, was considered one of the most important sources of hydroxyl radicals (OH), which are regarded as the detergent of the atmosphere, allowing the air to clean itself. ...

Better thermal-imaging lens from waste sulfur

Sulfur left over from refining fossil fuels can be transformed into cheap, lightweight, plastic lenses for infrared devices, including night-vision goggles, a University of Arizona-led international team ...

Hackathon team's GoogolPlex gives Siri extra powers

(Phys.org) —Four freshmen at the University of Pennsylvania have taken Apple's personal assistant Siri to behave as a graduate-level executive assistant which, when asked, is capable of adjusting the temperature ...