How AI could revolutionize prediction of deadly dust storms in Asia – Times of India
April 15, 2024
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NEW DELHI: With spring’s arrival in the Northern Hemisphere, parts of Asia are once again grappling with the annual menace of dust storms, which have recently shrouded regions like China’s Inner Mongolia in a thick yellow haze. On March 27, 2024, residents of Erenhot, Inner Mongolia, witnessed their skies turn murky, with state media advising people to stay indoors as winds whipped up dust with speeds reaching 100 kilometers per hour, reducing visibility to less than 90 meters.
This persistent problem has prompted significant scientific engagement, particularly from Chinese researchers who have been at the forefront of developing forecasting systems for these potentially deadly natural phenomena.The latest advancements involve the application of artificial intelligence (AI) and climate modeling aimed at improving the accuracy and timeliness of dust storm predictions, a report in science journal Nature said.
Chen Siyu, an atmospheric scientist at Lanzhou University, detailed the impact of dust storms, noting, “The dust and wind can combine to create massive, fast-moving walls of dust that travel a great distance.” These storms are not just vast curtains of dust; they also carry bacteria and toxic metals, posing serious health and environmental hazards. In fact, during such events, mortality from cardiovascular diseases can surge by 25%, and respiratory problems by 18%.
Chen’s team at Lanzhou University has developed an early-warning system named the Dust Watcher, utilizing AI to predict the timing and severity of incoming dust storms up to 12 hours in advance across 13 Asian countries. “AI can learn how dust storms evolve in time and space from a large amount of data,” explained Huang Jianping, a distinguished professor at the university. In a trial run, the Dust Watcher achieved 13% fewer errors compared to non-AI models.
Despite the challenges of forecasting, innovations like the Dust Watcher are proving to be crucial. Wang Zifa, an atmospheric physicist at the Chinese Academy of Sciences, emphasized the severe effects of dust storms in East Asia due to the region’s dense population. The efforts to refine these predictions are continuous, with Jin Jianbing from Nanjing University of Information Science and Technology developing a 48-hour forecast system that integrates observational data dynamically to enhance prediction accuracy, the Nature report said.
The relationship between climate change and dust storms adds another layer of complexity. While some studies suggest that climate phenomena like Arctic amplification might reduce dust levels by altering wind patterns, others indicate changing climate conditions could exacerbate the situation. Gao Meng, a co-author of a recent study, highlighted the delicate balance climate change plays in influencing dust storm patterns.
This persistent problem has prompted significant scientific engagement, particularly from Chinese researchers who have been at the forefront of developing forecasting systems for these potentially deadly natural phenomena.The latest advancements involve the application of artificial intelligence (AI) and climate modeling aimed at improving the accuracy and timeliness of dust storm predictions, a report in science journal Nature said.
Chen Siyu, an atmospheric scientist at Lanzhou University, detailed the impact of dust storms, noting, “The dust and wind can combine to create massive, fast-moving walls of dust that travel a great distance.” These storms are not just vast curtains of dust; they also carry bacteria and toxic metals, posing serious health and environmental hazards. In fact, during such events, mortality from cardiovascular diseases can surge by 25%, and respiratory problems by 18%.
Chen’s team at Lanzhou University has developed an early-warning system named the Dust Watcher, utilizing AI to predict the timing and severity of incoming dust storms up to 12 hours in advance across 13 Asian countries. “AI can learn how dust storms evolve in time and space from a large amount of data,” explained Huang Jianping, a distinguished professor at the university. In a trial run, the Dust Watcher achieved 13% fewer errors compared to non-AI models.
Despite the challenges of forecasting, innovations like the Dust Watcher are proving to be crucial. Wang Zifa, an atmospheric physicist at the Chinese Academy of Sciences, emphasized the severe effects of dust storms in East Asia due to the region’s dense population. The efforts to refine these predictions are continuous, with Jin Jianbing from Nanjing University of Information Science and Technology developing a 48-hour forecast system that integrates observational data dynamically to enhance prediction accuracy, the Nature report said.
The relationship between climate change and dust storms adds another layer of complexity. While some studies suggest that climate phenomena like Arctic amplification might reduce dust levels by altering wind patterns, others indicate changing climate conditions could exacerbate the situation. Gao Meng, a co-author of a recent study, highlighted the delicate balance climate change plays in influencing dust storm patterns.
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