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25 August 2021

Welcome back to AWIPS Tips! Today we're going to go over a brief overview of the backend component of AWIPS: EDEX. EDEX is the Environmental Data Exchange system that comprises the server side of AWIPS; it handles functions such as requesting raw data, decoding and ingesting data, storing processed data, and dealing with data requests from CAVE and python-awips connections.[Read More]

Posted by Nicole Corbin

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Offer: Unidata Science Gateway JupyterHub Resources Available for Fall 2021 Courses

23 August 2021

For the fall 2021 term, Unidata is once again offering to provide universities (or individual instructors) access to cloud-based JupyterHub servers tailored to the needs of university atmospheric science courses and workshops. By using the Unidata Science Gateway, instructors can add Jupyter notebooks used in their coursework to a dedicated JupyterHub hosted using Unidata's resources in the NSF Jetstream cloud. Once logged in to the JupyterHub, individual students access pre-configured computing environments that allow them to work with the notebooks interactively, making and saving their own alterations to existing notebooks or creating their own new notebooks.

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Posted by Unidata News

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AWIPS TIPS: Explore the CAVE Volume Browser: Plan Views

11 August 2021

Welcome back to AWIPS Tips! Today's focus is on CAVE'S Volume Browser. The Volume Browser is a tool for accessing model output and point sources like RAOB, METAR, and Profiler datasets. Rather than choosing from the preconfigured options in the default Data Menus, the Volume Browser allows you to select the exact sources, fields, planes, or points to display. The Volume Browser also has options for vertical cross sections, time series, and other display types, but today we will focus specifically on the default display type: plan views.

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Posted by Nicole Corbin

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MetPy 1.1.0 Released

09 August 2021

Version 1.1.0 of MetPy, a collection of tools in Python for reading, visualizing, and performing calculations with weather data, has been released. The project aims to mesh well with the rest of the scientific Python ecosystem, including the Numpy, Scipy, and Matplotlib projects, adding functionality specific to meteorology. This release includes a variety of new features and enhancements, as well a variety of fixes for issues encountered by users.

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Posted by Ryan May