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Soroosh Sorooshian
University of California, IrvineMeeting roles in:
Performance of Satellite-Derived Precipitation Products over the Santa Ana River Basin for Reservoir Operations at Prado Dam
Spatial Assessment of Two Satellite Rainfall Products Using Quality Controlled Ground-Based Interpolation in Saudi Arabia: Revealing the Need for Regional Bias Correction
Leveraging Passive Microwave Data (MiRS) With U-Net Architecture for Satellite Rainfall Estimation in High-Latitude Regions: A Case Study over Alaska
Regional Kilometer-Scale Data-Driven Precipitation Forecasting over the Western United States Using Artificial Intelligence (AI)
Scalable and Accurate Global River Streamflow Forecasting with Transformers
PUnet-CDR: A Deep Learning Framework for Reconstructing High-Resolution Global Precipitation Climate Data Records
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