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Kei Yoshimura
The University of TokyoMeeting roles in:
Application of a Real-Time Data Assimilation System to Enhance Flood Forecasts in Japan
Refining the Assessment of the “Dry Gets Drier, Wet Gets Wetter” Paradigm Using a Budyko-Based Approach with Global Hydrological Simulation Data
A Process-Guided Machine Learning Approach Improves Stomatal Conductance Prediction and Reveals Its Dynamic Association With Photosynthesis
Enhancing Parameter Calibration in Land Surface Models Using a Multi-Task Surrogate Model within a Differentiable Parameter Learning Framework
Water Isotope Model Intercomparison Project (WisoMIP): Present-day Climate
Improvement of Simulating GPP and ET in the Land Surface Model Based on Parameter Sensitivity Analysis and Calibration
Development of a Three-dimensional groundwater flow model for application to large scale problem
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