<strong>Improving AMSR2 snow depth retrieval through interpretable machine learning for enhanced snow drought assessment </strong>

Kehan Yang

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-HW Hydrology & Water Environment

[A-HW37] Global Drought Stress from Headwaters to Lowlands

Wed. May 27, 2026 10:45 AM - 12:15 PM 101 (International Conference Hall, Makuhari Messe)

Chairperson:Livneh Ben(University of Colorado Boulder), Schilling S. Oliver(Hydrogeology, Department of Environmental Sciences, University of Basel, Switzerland), Mankin S Justin(Dartmouth College), Yulizar Yulizar(National Taiwan University), Cook Benjamin(NASA Goddard Institute for Space Studies)

12:00 PM - 12:15 PM

[AHW37-06] Improving AMSR2 snow depth retrieval through interpretable machine learning for enhanced snow drought assessment

*Kehan Yang^1,2, Sujay V. Kumar², Goutam Konapala³, Justin M. Pflug^4,2, Carrie M. Vuyovich², Ehsan Jalilvand^5,2, Yeosang Yoon^5,2, Wegiel W. Jerry^5,2 (1. Science Systems and Applications, Inc., Lanham, MD, USA., 2. Hydrological Sciences Lab, NASA Goddard Flight Center, Greenbelt, MD, USA, 3. Pacific Northwest National Laboratory, Ames, Iowa, USA., 4. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA, 5. Science Applications International Corporation, McLean, VA, USA.)

Keywords:Snow depth, Snow drought, AMSR2, Interpretable machine learning