
Biosphere-Atmosphere Interactions
How vegetation dynamics influence and respond to climate through biogeophysical and biogeochemical feedbacks.
We investigate Earth system processes and global change to provide scientific evidence for climate mitigation, adaptation, and sustainable development.


How vegetation dynamics influence and respond to climate through biogeophysical and biogeochemical feedbacks.

Machine learning, deep learning, and explainable AI for climate data reconstruction, risk detection, attribution, and prediction.

Satellite remote sensing, ground observations, and Earth system models for global environmental change.

Quantifying climate impacts on terrestrial ecosystems, hydrology, and human systems.

Forestation, wetland restoration, forest management, and renewable energy pathways.

Multi-source satellite imagery for forests, urbanization, agricultural expansion, and environmental consequences.
A source-supported course listed in the PI's teaching and advising experience.
A source-supported course listed in the PI's teaching and advising experience.
A global monthly evapotranspiration dataset at 0.5 degree resolution from 1982 to 2009, built by coupling a water balance model with machine learning.
A global gridded monthly wind speed dataset using partial convolutional neural networks, HadISD observations, and 34 climate models for 1973-2021.
Code resources for multi-greenhouse-gas assessments in wetland restoration and greenhouse gas mitigation studies.
Code resources for assessing energy production and water savings from floating solar photovoltaics on global reservoirs.