Prof. Huaan Jin | Biophysical Parameters | Excellence in Innovation Award

Prof. Huaan Jin | Biophysical Parameters | Excellence in Innovation Award

Institution of Mountain Hazards and Environment, Chinese Academy of Sciences | China 

His research integrates satellite remote sensing, eco-hydrological modeling, and machine learning to estimate key Biophysical Parameters such as leaf area index, gross primary productivity, and fraction of absorbed photosynthetically active radiation. He has contributed to the development of high-resolution vegetation products by combining multisource satellite data with deep learning approaches. His work advances methodological frameworks for accurate environmental monitoring in mountainous regions. He has authored a scholarly book on mountain remote sensing and published extensively in leading international journals. His research supports improved understanding of mountain ecosystem functioning under environmental and climatic variability. In addition, his studies address data fusion, scaling, and uncertainty analysis in complex terrain. He has made methodological contributions to time-series analysis of satellite observations. His research provides valuable scientific support for ecosystem modeling and climate-related environmental assessments.

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Modeling canopy reflectance over sloping terrain based on path length correction
IEEE Transactions on Geoscience and Remote Sensing, 2017

Prof. Jin-Song von Storch | climate dynamics | Research Excellence Award

Prof. Jin-Song von Storch | Computational Neuroscience | Research Excellence Award 

Max-Planck Institute for Meteorology | Germany

Jin-Song von Storch is an internationally recognized Computational Neuroscience known for her contributions to understanding climate variability, predictability, and the dynamics of the coupled ocean–atmosphere system. Her research focuses on ocean energetics, internal waves, mesoscale eddies, and their role in large-scale circulation and climate sensitivity. She has made influential advances in stochastic climate theory, equilibrium fluctuations, and the statistical interpretation of climate variability. A key aspect of her work is the use of high-resolution and eddy-resolving Earth system models to investigate air–sea interactions and oceanic energy pathways. Her research has significantly improved the representation of ocean processes in climate models and informed international modeling efforts. Through a strong combination of theory, numerical modeling, and statistical analysis, her work bridges fundamental climate physics and applied climate prediction. She has authored a substantial body of highly cited publications across leading journals in climate science and physical oceanography. In addition to her scientific contributions, she has played an important leadership role in large collaborative research initiatives. She is also recognized for mentoring early-career researchers and shaping research directions in climate dynamics.

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