New Technique to Detect Storms, Predict Weather Changes

A woman stands in falling snow in front of an electronic sign displaying the weather forecast in Times Square in New York City on Jan. 26, 2015. Reuters
A woman stands in falling snow in front of an electronic sign displaying the weather forecast in Times Square in New York City on Jan. 26, 2015. Reuters
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New Technique to Detect Storms, Predict Weather Changes

A woman stands in falling snow in front of an electronic sign displaying the weather forecast in Times Square in New York City on Jan. 26, 2015. Reuters
A woman stands in falling snow in front of an electronic sign displaying the weather forecast in Times Square in New York City on Jan. 26, 2015. Reuters

A team of researchers from the Universities of Pennsylvania in the US and Almería in Spain, and AccuWeather, Inc. has developed a new computer model that can help forecasters recognize potential severe storms more quickly and accurately.

According to the German News Agency, the new computer model relies on artificial intelligence that detects rotational movements in clouds from satellite images.

When forecasting weather, meteorologists use a number of models and data sources to track shapes and movements of clouds that could indicate severe storms. However, with increasingly expanding weather data sets and looming deadlines, it is nearly impossible for them to monitor all storm formations, especially smaller-scale ones, in real time.

The Science Daily website cited Steve Wistar, senior forensic meteorologist at AccuWeather, saying that having this tool to point the eye toward potentially threatening formations could help in making a better forecast.

In their study, the researchers analyzed more than 50,000 historical weather satellite images. In them, experts identified and labeled the shape and motion of "comma-shaped" clouds that can lead to severe weather.

Then, the researchers fed the artificial intelligence system with these images, in order to teach it how to automatically recognize and detect the comma-shaped clouds in satellite images. The computers can then assist experts by pointing out in real time where to focus their attention in order to detect the onset of severe weather.

The researchers found that their method can effectively detect pre-storm clouds with 99 percent accuracy, at an average of 40 seconds per prediction. It was also able to predict 64 percent of severe weather events, outperforming other existing severe-weather detection methods.



Syria Seeks EU Help to Battle Massive Wildfires

FILE : A fire burns at a forest in Latakia province, Syria in this handout released by SANA on October 9, 2020. SANA/Handout via REUTERS
FILE : A fire burns at a forest in Latakia province, Syria in this handout released by SANA on October 9, 2020. SANA/Handout via REUTERS
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Syria Seeks EU Help to Battle Massive Wildfires

FILE : A fire burns at a forest in Latakia province, Syria in this handout released by SANA on October 9, 2020. SANA/Handout via REUTERS
FILE : A fire burns at a forest in Latakia province, Syria in this handout released by SANA on October 9, 2020. SANA/Handout via REUTERS

Syria’s minister of emergencies and disaster management on Tuesday requested support from the European Union to battle wildfires that have swept through a vast stretch of forested land.

The fires have been burning for six days, with Syrian emergency crews struggling to bring them under control amid strong winds and severe drought.

Neighboring countries Jordan, Lebanon and Türkiye have already dispatched firefighting teams to assist in the response.

“We asked the European Union for help in extinguishing the fires,” minister Raed al-Saleh said on X, adding Cyprus was expected to send aid on Tuesday, AFP reported.

“Fear of the fires spreading due to strong winds last night prompted us to evacuate 25 families to ensure their safety without any human casualties,” he added.

According to the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) office in Syria, the fires impacted “some 5,000 persons, including displacements, across 60 communities.”

An estimated 100 square kilometers (40 square miles) of forest and farmland -- more than three percent of Syria’s forest cover -- have burned, OCHA told AFP.

At least seven towns in Latakia province have been evacuated as a precaution.

Efforts to extinguish the fires have been hindered by “rugged terrain, the absence of firebreaks, strong winds, and the presence of mines and unexploded ordnance”, Saleh said.

With man-made climate change increasing the likelihood and intensity of droughts and wildfires worldwide, Syria has also been battered by heatwaves and low rainfall.

In June, the United Nations Food and Agriculture Organization said Syria had “not seen such bad climate conditions in 60 years.”