Global Risks

Why satellite data could revolutionize hurricane monitoring

Dark clouds pass over downtown Miami, Florida August 15, 2010. An area of low pressure over southwest Georgia could move southward into Gulf of Mexico waters by early Monday and has a medium chance of becoming a tropical cyclone in the next 48 hours, the National Hurricane Center said on Sunday. The low pressure area was the remnant of Tropical Depression Five which dissipated on Wednesday in the Gulf. The U.S. Gulf of Mexico is home to about 30 percent of U.S. oil production, 11 percent of natural gas production, and more than 43 percent of U.S. refinery capacity.

Image: REUTERS/Carlos Barria

Liam Jackson
Marketing Communications Specialist, Penn State College of Earth and Mineral Sciences
Share:
Our Impact
What's the World Economic Forum doing to accelerate action on Global Risks?
The Big Picture
Explore and monitor how Global Risks is affecting economies, industries and global issues
A hand holding a looking glass by a lake
Crowdsource Innovation
Get involved with our crowdsourced digital platform to deliver impact at scale
Stay up to date:

Global Risks

The launch of the GOES-R geostationary satellite in October 2016 could offer a whole new way to predict hurricanes, providing information at time and space scales not previously possible.

“For decades, geostationary satellites such as the GOES series have been the primary tool to monitor severe weather like storms and hurricanes in real time,” says Fuqing Zhang, professor of meteorology at Penn State.

“They have helped people see what’s going on in the present, but, until now, we as a community have not been able to tap into these resources to guide us to predict future severe weather.”

Geostationary satellites like the GOES series orbit the Earth at a fixed location, taking snapshots of cloud formations and other meteorological information. The National Oceanic and Atmospheric Administration operates GOES with contributions from NASA.

Historically, two main challenges exist when using satellite data for hurricane predictions—the type and amount of data collected. Satellites don’t directly measure many quantities related to a hurricane’s intensity, such as surface pressure, wind speeds, temperature, and water vapor beneath the cloudy regions of the hurricane eyewall.

They do, however, collect data known as brightness temperature, which show how much radiation is emitted by objects on Earth and in the atmosphere at different infrared frequencies. Because all objects naturally emit and absorb different amounts of radiation at different frequencies, the complexity of data poses challenges to researchers hoping to use these data for hurricane prediction models.

“At some frequencies water vapor absorbs moderate amounts of radiation passing through it, at other frequencies it absorbs most of that radiation, and at other frequencies it absorbs hardly any at all,” says Eugene Clothiaux, professor of meteorology.

“Unlike water vapor, clouds strongly absorb radiation at all of these frequencies. Comparing measurements at different frequencies leads to information about water vapor and clouds at different altitudes above the Earth. This begins to tell us about the physical structure of water vapor fields and clouds, including those in the area around a hurricane.”

Brightness data

Using brightness temperature satellite data to improve model forecasts of hurricanes is not straightforward. Brightness temperature information is a complex mixture related to the ground, atmospheric water vapor, and clouds. Researchers had to develop a sophisticated analysis and modeling scheme to extract information in useful ways for model forecasts.

The team demonstrated in a pilot study that it is becoming feasible to use brightness data. They found definitive correlations between measurements of brightness temperature and information about the storm—wind speed and sea level pressure underneath the hurricane. Their findings are reported in the current issue of Geophysical Research Letters.

Using data from GOES-13, the team completed a proof-of-concept experiment, analyzing data from Hurricane Karl in 2010. They used the real-time hurricane analysis and prediction system that Zhang and his team have been developing and refining for nearly a decade.

“Hurricane prediction models work by chunking individual blocks of the hurricane and this starts from the initial information that is fed into the model,” says Zhang. “We then run an ensemble of possible outcomes for the hurricane using different variables to estimate uncertainty and this tells us how the hurricane might behave. If we are able to use a higher resolution for the initial state, this could allow us to vastly improve hurricane predictions in the future.”

GOES-13 provides data at a resolution of 2.5 miles, and GOES-R will increase that to under 0.6 miles for some frequencies of brightness temperature. The increase in resolution is especially important because of the size of hurricanes. The eyewall, the layer of clouds surrounding the eye, varies in size but is roughly 6 miles thick. Using GOES-13 brightness temperatures with 2.5-mile resolution, the eyewall is often grouped together with other parts of the storm, with only one or two brightness temperature measurements from only the eyewall itself.

A 0.6-mile resolution brightness temperature measurement would allow for up to 10 eyewall measurements to be fed into prediction models as separate chunks of information instead of grouped together with other parts of the storm.

This new data source could have implications on the longstanding challenge of predicting hurricane intensity, Zhang says. Researchers know that wind speed and other levels of activity near the eye of the hurricane are linked to future intensity, but actually collecting these data is difficult. Today, NOAA uses airborne reconnaissance to collect data, but this is only possible when the storm is within flying distance. Satellites that constantly monitor the oceans at high spatial and temporal resolution and with many frequencies of brightness temperature, like GOES-R, could remove that constraint.

“Geostationary satellites are there all the time, which makes them ideal for capturing the initial and evolving states of hurricanes, including the crucial information in the cloudy region of the storm,” Zhang says. “Using satellite data more effectively could potentially revolutionize hurricane monitoring and prediction for many years.”

The National Science Foundation, the Office of Naval Research, NASA and the Funai Foundation for Information Technology supported this research.

Don't miss any update on this topic

Create a free account and access your personalized content collection with our latest publications and analyses.

Sign up for free

License and Republishing

World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

Related topics:
Global RisksFourth Industrial Revolution
Share:
World Economic Forum logo
Global Agenda

The Agenda Weekly

A weekly update of the most important issues driving the global agenda

Subscribe today

You can unsubscribe at any time using the link in our emails. For more details, review our privacy policy.

Global financial stability at risk due to cyber threats, IMF warns. Here's what to know

Spencer Feingold and Johnny Wood

May 15, 2024

About Us

Events

Media

Partners & Members

  • Join Us

Language Editions

Privacy Policy & Terms of Service

© 2024 World Economic Forum