A collaborative international research team led by Professor Yoo-Geun Ham from Chonnam National University and Professor Seung-Ki Min from Pohang University of Science and Technology has made a discovery on the impact of global warming on global daily precipitation. Using a deep learning approach, they have unveiled a significant change in the characteristics of global daily precipitation for the first time.
In contrast to conventional studies, which primarily focus on long-term trends in monthly or annual precipitation, the researchers employed explainable artificial intelligence to demonstrate that changes in daily precipitation variations were gradually intensifying upon weather timescales. These fluctuations in rainfall at this weather time scale served as the most conspicuous indicators of global warming.
The researchers explained that traditional linear statistical methods used in previous climate change detection research had limitations in discerning non-linear reactions such as the intensified variability in daily precipitation. Deep learning, however, overcame these limitations by employing non-linear activation functions.
Professor Yoo-Geun Ham explained,"Intensification of day-to-day precipitation variability implies an increase in the frequency of extreme precipitation events as well as a higher occurrence of heatwaves during the summer due to extended dry spells.
This study was conducted with the support from the Ministry of Environment and the National Research Foundation of Korea.
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