Representation of nodes in a Self Organizing Map.

A self-organizing map (SOM), sometimes known as a Kohonen map after its originator the Finnish professor Teuvo Kohonen, is an unsupervised machine learning technique used to produce a low-dimensional representation of a higher dimensional data set. SOMs are a specific type of artificial neural network, but use a different training strategy compared to more traditional artificial neural networks (ANNs). SOMs can be used for clustering, dimensionality reduction, feature extraction, and classification — all of which suggest that they can be important tools for understanding large Earth Systems Science (ESS) datasets.

The National Science Foundation (NSF) is seeking public input from the science and engineering research and education community on implementing the NSF Public Access Plan 2.0.

The Public Access Plan 2.0 is an update to NSF current public access requirements in response to recent White House Office of Science and Technology Policy guidance; among other things, it addresses potential equity impacts of public access requirements.

The Unidata Program Center is partnering with UCAR's COSMIC program to provide radio occultation data provided by Spire Global. The products described below are now available via the Internet Data Distribution (IDD) network. Data are on the EXP feed with a typical total volume of 80-110 MB per hour.

Everyone loves to talk about the weather. But until now, serious collectors of weather memorabilia have been left on the sidelines. Oh, a lucky few manage to save enormous hailstones in their freezers, but most are limited to screen shots of satellite or radar imagery, or maybe articles clipped from the local newspaper.

But never fear: Unidata is preparing to bring weather collectibles into the twenty-first century by minting a series of Non Fungible Tokens (NFTs) based on significant weather events. Our inaugural series will consist of 902 distinct NFTs of Hurricane Katrina, one for each millibar of the storm's lowest recorded atmospheric pressure.

The Unidata program and the University of Wisconsin–Madison's Space Science and Engineering Center (SSEC) have a long history of collaboration and cooperation to serve the needs of Unidata community members. The SSEC Satellite Data Services(SDS) group, which provides access to and distribution of real-time and archive weather satellite data, makes limited amounts of archive satellite data available to Unidata's academic community members at no cost via the “Multi-format Client-agnostic File Extraction Through Contextual HTTP” (MCFETCH) system.