The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Harmonizing Global Geostationary Imagery with Deep Learning for Near Real-Time Precipitation Tracking (AGU25)

Harmonizing Global Geostationary Imagery with Deep Learning for Near Real-Time Precipitation Tracking

Yeji Choi1, Hyungon Ryu2, Kwang-Min Myung1, Seongryeong Choi1, Jiu Park1 and Yong-Jae Moon3, (1)DI Lab Inc., Seoul, South Korea, (2)NVIDIA, Seoul, South Korea, (3)School of Space Research, Kyung Hee University, Yongin, South Korea
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