Date: November 1, 2024
Location: Room 1223,College of Forestry, Wildlife and Environment
Time: 13:00 – 15:00
Title: Addressing climate resilience through AI-improved hydroclimate observations, predictions, and impact assessment
Attendees: 12
On November 1, 2024, Dr. Di Tian from Department of Crop, Soil, and Environmental Sciences delivered a presentation titled “Addressing climate resilience through AI-improved hydroclimate observations, predictions, and impact assessment”. The seminar, attended by 12 people in person and via Zoom, focused on addressing climate resilience through deep learning-improved hydroclimate observations and predictions.
Dr. Tian introduced a framework to improve the understanding, monitoring, and predictions of terrestrial hydroclimate processes, extreme events, and impacts using synergies of geoscientific first principles, ground and satellite remote sensing observations, process-based modeling, and artificial intelligence (AI)/machine learning (ML) approaches. He also presents several recent studies using this framework, covering climate model downscaling and bias correction, sub-seasonal-to-seasonal predictions and monitoring of droughts, and satellite-based evapotranspiration monitoring for water management.
This seminar and the subsequent Q&A session lasted two hours, followed by extensive questions and discussions from faculty and students. Dr. Tian’s work will inspire students to further investigate climate resilience or AI models in their own studies.
We thank Dr. Tian for his engaging presentation and look forward to more discussions, research efforts, and collaborations in climate change, deep learning, and related fields!