Version 5.3.4 of the netCDF Operators (NCO) has been released. NCO is an Open Source package that consists of a dozen standalone, command-line programs that take netCDF files as input, then operate (e.g., derive new data, average, print, hyperslab, manipulate metadata) and output the results to screen or files in text, binary, or netCDF formats.
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.
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.
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.
Version 5.3.3 of the netCDF Operators (NCO) has been released. NCO is an Open Source package that consists of a dozen standalone, command-line programs that take netCDF files as input, then operate (e.g., derive new data, average, print, hyperslab, manipulate metadata) and output the results to screen or files in text, binary, or netCDF formats.
We are happy to announce a new version of python-awips (v23.1) is available! This version is available via source code (with all example notebooks) or via mamba (conda) and pip. Please see our main documentation page for installation instructions.
Version 5.3.2 of the netCDF Operators (NCO) has been released. NCO is an Open Source package that consists of a dozen standalone, command-line programs that take netCDF files as input, then operate (e.g., derive new data, average, print, hyperslab, manipulate metadata) and output the results to screen or files in text, binary, or netCDF formats.
The NCO project is coordinated by Professor Charlie Zender of the Department of Earth System Science, University of California, Irvine. More information about the project, along with binary and source downloads, are available on the SourceForge project page.
If you provide Earth Systems Science learning opportunities at the post-secondary levels or within the workforce, UCAR needs your input! UCAR would love to hear about any learning opportunities that you offer on emerging ESS capabilities — ranging from AI/ML and data management to relationship building, creativity, and more — that are needed in the workplace now and in the future. Help UCAR understand your priorities and any obstacles to providing education, training, and support for these capabilities.
Do you know someone in the NSF Unidata community who has been actively involved and helpful to you and other NSF Unidata members? Perhaps this is someone who volunteers to assist others, contributes software, or makes suggestions that are generally useful for the community.
The NSF Unidata Users Committee invites you to submit nominations for the Russell L. DeSouza Award for Outstanding Community Service. This Community Service Award honors individuals whose energy, expertise, and active involvement enable the NSF Unidata Program to better serve the Earth Systems Sciences community. Honorees personify NSF Unidata's ideal of a community that shares ideas, data, and software through computing and networking technologies.
