15 citations · 26 across the 5 of their papers we have counts for
6 papers
Partial recovery of meter-scale surface weather
Jonathan Giezendanner, Qidong Yang, Eric Schmitt +9
Near-surface weather varies over tens to hundreds of meters, yet remains unresolved in analyses and forecasts. We test whether this variation can be inferred without resolving atmo…
Enhancing operational wind downscaling capabilities over Canada: Application of a Conditional Wasserstein GAN methodology
Jorge Guevara, Victor Nascimento, Johannes Schmude +4
Wind downscaling is essential for improving the spatial resolution of weather forecasts, particularly in operational Numerical Weather Prediction (NWP). This study advances wind do…
Local Off-Grid Weather Forecasting with Multi-Modal Earth Observation Data
Qidong Yang, Jonathan Giezendanner, Daniel Salles Civitarese +8
Urgent applications like wildfire management and renewable energy generation require precise, localized weather forecasts near the Earth's surface. However, forecasts produced by m…
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…
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation
S. Karthik Mukkavilli, Daniel Salles Civitarese, Johannes Schmude +12
Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been incr…
TensorBank: Tensor Lakehouse for Foundation Model Training
Romeo Kienzler, Leonardo Pondian Tizzei, Benedikt Blumenstiel +9
Storing and streaming high dimensional data for foundation model training became a critical requirement with the rise of foundation models beyond natural language. In this paper we…