9 citations · 9 across the 6 of their papers we have counts for
6 papers
Prithvi-Precip: Integrating Satellite Observations into an Atmospheric AI Foundation Model for Precipitation Forecasting
Simon Pfreundschuh, Christian D. Kummerow, Johannes Schmude +5
Accurate precipitation forecasting remains one of the most challenging problems in weather prediction. While recent AI weather prediction (AIWP) systems have achieved substantial i…
GPROF-IR: An Improved Single-Channel Infrared Precipitation Retrieval for Merged Satellite Precipitation Products
Simon Pfreundschuh, Christian D. Kummerow, Jackson Tan +1
The Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement (IMERG) product combines precipitation estimates from passive microwave (PMW) and infrared (IR) s…
Bridging the Sensitivity Gap in Precipitation Estimates from Spaceborne Radars using Passive Microwave Observations
Simon Pfreundschuh, Christian D. Kummerow
Current global precipitation estimates from spaceborne precipitation radars are limited by their sensitivity to light and frozen precipitation, leading to systematic underestimatio…
A Benchmark Dataset for Satellite-Based Estimation and Detection of Rain
Simon Pfreundschuh, Malarvizhi Arulraj, Ali Behrangi +17
Accurately tracking the global distribution and evolution of precipitation is essential for both research and operational meteorology. Satellite observations remain the only means…
WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks
Rajat Shinde, Christopher E. Phillips, Kumar Ankur +10
High-quality machine learning (ML)-ready datasets play a foundational role in developing new artificial intelligence (AI) models or fine-tuning existing models for scientific appli…
Prithvi WxC: Foundation Model for Weather and Climate
Johannes Schmude, Sujit Roy, Will Trojak +26
Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing numbe…