GOES Rebroadcast User Survey

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NOAA's Satellite Products and Services Division is looking for feedback on community use of the GOES Rebroadcast system (GRB).

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netCDF vs Zarr, an Incomplete Comparison

Visualization created from netCDF data

At NSF Unidata, we have been supporting and developing netCDF standards and packages since the original release of netCDF in 1990. We strongly believe in the usefulness of netCDF Common Data Model for Earth Systems Science data, and for other types of data! NetCDF files can be used efficiently in machine learning modeling applications and can be used as a virtual Zarr datasets.

NSF Unidata has been urged by our community to investigate options to allow netCDF to work more easily with modern cloud-based infrastructure. Based on the strong interest and rapid adoption of Zarr by the community, the netCDF team decided to begin working with the Zarr community to ensure that these two widely used data storage mechanisms can interoperate if necessary.

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Convolutional Neural Networks (CNNs) for Earth Systems Science

Process of conovolving a filter with an image

Convolutional Neural Networks (CNNs) are a powerful class of deep learning models widely applied in Earth science for image analysis, classification, and regression problems. Leveraging the Keras framework in python, CNNs can efficiently process and extract spatial features from 2D and 3D remote sensing, model output, and other Earth Systems Science (ESS) data types.

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SSEC Unidata Server Has Been Shut Down!

The NSF Unidata server hosted at the Space Science and Engineering Center (SSEC) at the University of Wisconsin, Madison (unidata3.ssec.wisc.edu) has been permanently decommissioned.

Those who used the services provided by unidata3.ssec.wisc.edu should switch to the following alternate servers:

Service If you used Switch to
McIDAS ADDE adde.ssec.wisc.edu adde.ucar.edu
IDD/LDM Upstream idd.ssec.wisc.edu idd.unidata.ucar.edu
HTTP access to IDD Data atm.ucar.edu

Please reach out to us at support@unidata.ucar.edu if you have any questions!

Why is the Keras 3 Release a Big Deal for the Deep Learning Community?

Chart depicting use of different machine learning frameworks

The Keras package is an open-source library that provides a Python interface for deep learning. Keras is intended to be a user-friendly, modular, and extensible way to enable fast experimentation with deep neural networks. With Keras version 3, the package provides APIs for using three backends: TensorFlow, Jax, and PyTorch.

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News and information from the Unidata Program Center
News@Unidata
News and information from the Unidata Program Center

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