Due to the current gap in continued funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program Center has temporarily paused most operations. See NSF Unidata Pause in Most Operations for details.
NSF Unidata Pause in Most Operations
09 May 2025
Due to the current gap in funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program is pausing most operations. Nearly all staff will be furloughed until funds from our existing NSF grant become available.
[Read More]netCDF-Java version 5.8.0 released
08 May 2025
The NSF Unidata THREDDS development team released netCDF-Java 5.8.0 on May 8th, 2025. This release contains a number of upgrades to third party libraries, a variety of bug fixes, and several new features and improvements.
[Read More]New eLearning: Supervised Machine Learning Readiness
07 May 2025
Announcing a new eLearning series available now on Unidata eLearning: Supervised Machine Learning Readiness. This learning series is a self-paced, beginner-friendly program designed for Earth systems scientists to explore the core principles of supervised machine learning. This series uses a combination of step-by-step frameworks, exploratory widgets, and low-code exercises in Jupyter Notebooks, to explore the full cycle of machine learning model development. No programming experience is required. By the end of the series, you will be able to recognize when machine learning is an appropriate tool and critically evaluate machine learning in Earth systems science contexts.
[Read More]Running Pretrainined AI-NWP Models, Our Experience at NSF Unidata on Jetstream2
07 May 2025
At NSF Unidata, we have successfully implemented and re-used weights from several global AI-NWP (Artificial Intelligence-Numerical Weather Prediction) models (FourCastNet, Pangu) using the NVIDIA earth2mip package. We can confirm that these models are open source and can be reused on high-end, but increasingly standard, HPC hardware. While traditional numerical weather prediction requires massive supercomputing resources, these AI models can potentially deliver similar or better results using standard GPU hardware for inference.
[Read More]05 May 2025
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