Software systems require substantial set-up to get all the necessary code, including external libraries, compiled on a specific platform. Recently, the concept of containers has been gaining popularity because they allow for software systems to be bundled (including operating system, libraries, code, and executables) and provided directly to users, eliminating possible frustrations with up-front system setup. This course will provide information on using software containers that have been established for community use to quickly spin up an Numerical Weather Prediction (NWP) forecast system [using the Weather Research and Forecasting (WRF) model initialized with WRF Pre-processing System (WPS) and the Gridpoint Statistical Interpolation (GSI) data assimilation system] that can then be post-processed [using the Unified Post Processor (UPP)] and verified [using the Model Evaluation Tools (MET)]. Ultimately, the established containers substantially reduce the spin-up time with setting up and compiling software systems and promote greater efficiency in getting to the end goal of producing model output and statistical analyses.
The goal of this course is to raise awareness about tools and facilities available to the community for testing and evaluating of NWP innovations, including the emerging set of software tools in reusable containers.
While this course may appeal to a wide-reaching audience, this information may be particularly useful to undergraduate and graduate students interested in learning more about NWP and to university faculty that may find software containers to be a useful teaching tool to add to their course curriculum. In addition, researchers who wish to collaborate with others may find these tools useful for sharing a code base and replicating procedures even if they are not working on the same platform.
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