Predicting Unpredictable Weather

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Predicting Unpredictable Weather

Mason Engineering PhD student Leonardo Porcacchia remembers watching the news when he was growing up in Italy and seeing reports about weather hazards. He says the scenes and stories from his youth drove him to become a scientist of the atmosphere with a focus on precipitation.

Extreme weather events represent a serious problem everywhere in the world, particularly in remote regions that are not well equipped with instruments to predict these events and prepare for them.

Porcacchia’s research focuses on a peculiar precipitation process in the atmosphere, a process responsible for high-intensity rainfall rates at ground level.

“The process, called collision-coalescence, is like the snowball effect, except with raindrops. It works like this: Some drops in the cloud reach the point where they start to fall toward the

Assistant Professor Viviana Maggioni and her research team analyze satellite data to improve the characterization of precipitation around the globe.

Photo by Evan Cantwell

surface,” he says. “In their descent, if the right conditions are met, they collide with smaller drops, collect them, and become larger. It is like a snowball rolling down a hill and collecting fresh snow and becoming bigger and bigger.”

Collision-coalescence processes are very effective at increasing the amount of water that falls to the ground and may lead to fash foods, but they are often diffcult to detect. That’s why Porcacchia has been developing a classifcation scheme for identifying collision-coalescence scenarios that use observations from advanced radar to see inside clouds.

Recently, a new satellite mission dedicated to precipitation has been launched. The Global Precipitation Measurement (GPM) is a NASA-JAXA (Japanese Aerospace Exploration -Agency) satellite mission to provide next-generation obser vations of rain and snow worldwide every three hours.

The GPM Core Observatory satellite carries advanced instruments that set a new standard for precipitation measurements from space, including a Dual-frequency Polarimetric Radar (DPR). The data these tools provide is used to unify precipitation measurements made by an international network of partner satellites to quantify when, where, and how much it rains or snows around the world.

-“The GPM mission contributes to advancing our under standing of Earth’s water and energy cycles, improves the forecasting of extreme events, and extends current capabilities of using satellite precipitation information to directly beneft society,” says Viviana Maggioni, Porcacchia’s advisor and an assistant professor in the Sid and Reva Dewberry Department of Civil, Environmental, and Infrastructure Engineering. “Leonardo’s research aims at improving the DPR algorithm for precipitation estimation.”

“My classifcation scheme can be applied to the dataset collected by this space-borne radar, and therefore I am able to detect collision-coalescence processes at a global scale,” Porcacchia says.

“One of the signifcant limitations of remotely sensed data is the potential error associated with the data, especially in the case of precipitation systems triggered by orography, which yield signifcant nonmeteorological backscatter of the radar signal,” Maggioni says. “Leonardo’s work proposes a new algorithm to improve the classifcation -of precipitation regimes observed by radars and, conse quently, improve the estimation of rainfall rates to reduce those errors and uncertainties.”

Porcacchia thinks his classifcation scheme and this space-borne radar dataset together will improve real-time prediction of rainfall rates in cases of extreme events and help remote regions all over the world that cannot count on -local ground instruments. Particularly, it will help communi ties like those in Italy that frst inspired his work.

––Martha Bushong

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