This algorithm could help better predict extreme weather events

Researchers have developed an algorithm for measuring wind via water vapor.

Wind speed and direction provide clues for forecasting weather patterns. In fact, wind influences cloud formation by bringing water vapor together.

The new method could help predict extreme events like hurricanes and storms.

The study in the journal Geophysical Research Letters provides, for the first time, data on the vertical distribution of horizontal winds over the tropics and midlatitudes. The researchers got the water vapor movement data by using two operational satellites of the National Oceanic and Atmospheric Administration, or NOAA, the federal agency for weather forecasting.

Wind brings everything else in the atmosphere together, including clouds, aerosols, water vapor, precipitation, and radiation, says study coauthor Xubin Zeng, the director of the Climate Dynamics and Hydrometeorology Collaborative at the University of Arizona. But it has remained somewhat elusive.

“We never knew the wind very well. I mean, that’s the last frontier. That’s why I’m excited,” Zeng says.

Thanks to more advanced algorithms, Zeng says, the researchers were able to do the estimation of horizontal winds not just at one altitude, but at different altitudes at the same location. “This was not possible a decade ago,” he says.

Wind measurement typically is done in three different ways, Zeng explains. The first is through the use of radiosonde, an instrumental package suspended below a 6-foot-wide balloon. Sensors on the radiosonde measure wind speed and direction, and take measurements of atmospheric pressure, temperature, and relative humidity.

The downsides of radiosonde balloons, Zeng says, is the cost. Each launch could cost around $400 to $500, and some regions, such as Africa and the Amazon rainforest, have limited radiosonde stations. The other limitation is that radiosondes are not available over oceans, Zeng says.

Another way to measure wind is using cloud top, which is the height at which the upper visible part of the cloud is located, Zeng says. By tracking cloud top movement using geostationary satellite data, weather experts monitor wind speed and direction at one height.

But Zeng says cloud tops exist most of the time below 2 miles or above 4 1/2 miles above Earth’s surface, depending on whether the clouds are low or high. This means wind information is usually not available in the middle, between 2 and 4 1/2 miles.

Lidar, which stands for light detection and ranging, is a method that precisely measures wind movements at different elevations, and it provides very good data, Zeng says. But with lidar, measurements can be acquired only in one vertical “curtain,” with measured wind typically in the east-west direction, he adds.

Nowadays, Zeng says, to study topics like air quality and volcano ash dispersion, which are directly influenced by wind, experts use weather forecasting models to ingest measurements from different sources rather than using direct measurements of wind. But model outputs are not good enough when there is rainfall, Zeng says.

In the new study, Zeng and his team avoided using data from models. They instead used data from the movement of water vapor recorded by the two NOAA satellites. The satellites moved in the same direction separated by a 50-minute interval, and they detected the water vapor movement through infrared radiation.

While our eyes cannot detect the minute movements of water vapor in the atmosphere, lead study author Amir Ouyed, a member of Zeng’s research group, used machine-learning algorithms that do better image processing to track water vapor.

“For decades, people were saying, ‘You have to move the cloud top or water vapors enough so that you can see the difference of the pattern.’ But now, we don’t need to do that,” Zeng says.

“The resolution of the data is coarse, with a pixel size of 100 kilometers. It’s a demonstration of the feasibility for our future satellite mission we are pursuing where we hope to provide the 10-kilometer resolution,” Zeng says.

Zeng and his collaborators at other institutions are planning to pursue a new satellite wind mission in which they envision combining water vapor movement data and measurements from wind lidar to provide better wind measurements overall.

Source: University of Arizona