Wind is an essential factor in forecasting weather patterns, as it influences cloud formation by bringing water vapor together. Now, atmospheric scientists have discovered a groundbreaking method of measuring wind using an algorithm that interprets data from water vapor movements.
This innovative approach could prove invaluable in predicting extreme weather events such as hurricanes and storms.
For the first time, a study recently published in the journal Geophysical Research Letters provides insights into the vertical distribution of horizontal winds over tropical and midlatitude regions. The research was conducted by researchers at the University of Arizona.
The scientists obtained water vapor movement data by utilizing two operational satellites belonging to the National Oceanic and Atmospheric Administration (NOAA), the federal agency responsible for weather forecasting.
Wind plays a crucial role in bringing together various atmospheric elements, including clouds, aerosols, water vapor, precipitation, and radiation, explained Xubin Zeng, co-author of the study and the director of the Climate Dynamics and Hydrometeorology Collaborative at the University of Arizona. However, he noted that wind 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 said.
According to Zeng, the researchers’ ability to estimate horizontal winds at different altitudes in the same location is due to more advanced algorithms. “This was not possible a decade ago,” he added.
Zeng went on to explain that wind measurement is typically performed using three distinct methods. The first involves the use of radiosondes, which are instrumental packages suspended below a 6-foot-wide balloon. Sensors on the radiosonde measure wind speed and direction, as well as atmospheric pressure, temperature, and relative humidity.
However, Zeng highlighted several downsides of using radiosonde balloons. The cost of each launch can range from $400 to $500, and radiosonde stations are limited in certain regions, such as Africa and the Amazon rainforest. Additionally, he pointed out that radiosondes are not available for use over oceans.
This new method, combining data from geostationary satellites and lidar technology, could potentially revolutionize the way scientists study wind patterns and phenomena that are directly influenced by wind, such as air quality and volcanic ash dispersion.
Traditionally, meteorologists have used cloud top movement to measure wind at one height. However, according to researcher Xubin Zeng, cloud tops usually exist either below 2 miles or above 4 1/2 miles above Earth’s surface, leaving a gap in wind information between these two elevations.
Lidar (light detection and ranging) technology can provide precise measurements of wind movements at various heights, but its capabilities are limited to measuring wind in a single vertical “curtain,” primarily in the east-west direction.
To tackle air quality and volcanic ash dispersion issues, experts have had to rely on weather forecasting models that incorporate measurements from different sources instead of direct wind measurements.
New method measures movement of water vapor
Unfortunately, these models are not accurate enough when rainfall is present. In an attempt to bypass these limitations, Zeng and his team used data from the movement of water vapor recorded by two NOAA satellites.
These satellites, moving in the same direction and separated by a 50-minute interval, detected water vapor movement through infrared radiation. While the human eye cannot discern the subtle movements of water vapor in the atmosphere, lead study author Amir Ouyed and Zeng’s research group employed machine-learning algorithms to better process images and track the water vapor.
Zeng explained, “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.”
The current resolution of the data is coarse, with a pixel size of 100 kilometers. However, Zeng sees this as a promising start for a future satellite mission, stating, “It’s a demonstration of the feasibility for our future satellite mission we are pursuing where we hope to provide the 10-kilometer resolution.”
The ultimate goal is to combine water vapor movement data and measurements from wind lidar to deliver more accurate and comprehensive wind measurements overall.
Zeng and his collaborators at other institutions are currently working on the development of a new satellite wind mission to further enhance our understanding of wind patterns and to provide more accurate data to study phenomena influenced by wind.
This groundbreaking research holds the potential to significantly improve our ability to predict and respond to weather-related events, natural disasters, and air quality concerns. As extreme weather events become more frequent and severe, the importance of accurate predictions cannot be overstated.
Wind is the movement of air from areas of high pressure to areas of low pressure across the Earth’s surface. It is created due to the uneven heating of the Earth by the Sun, which results in variations in temperature and pressure across different regions.
The Sun’s energy heats the Earth’s surface, causing the air above it to warm up and expand. As warm air rises, it creates areas of low pressure near the surface.
Meanwhile, in cooler regions, the air is denser, and it sinks, creating areas of high pressure. Wind is the horizontal movement of air as it flows from high-pressure areas to low-pressure areas, attempting to equalize these pressure differences.
The Earth’s rotation, known as the Coriolis effect, also plays a role in the direction and speed of wind. In the Northern Hemisphere, the Coriolis effect causes winds to turn to the right, while in the Southern Hemisphere, winds turn to the left. This deflection is more pronounced at higher latitudes and less noticeable near the equator.
Other factors, such as the presence of large bodies of water, topography, and local weather conditions, can also influence wind patterns. Understanding wind is crucial for studying weather and climate, as well as for predicting and mitigating the impacts of natural disasters, air pollution, and other environmental issues.
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