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This project aims to advance and improve our STOFS event dashboard (github repo). This tool allows a user to select events (e.g., tropical cyclones, winter storms, major incidents in coastal areas) and compare STOFS model results with observations for those events. The tool is currently in a prototype phase, and the mentee would have an opportunity to contribute to design, backend implementation (event definition, processing data), and frontend (data visualization). Example contributions include:
Streamline user definition of events, e.g., by creating a command line interface that defines a config file that specifies space, time, physical variables, models, etc.
Add further sources of observational data (e.g., searvey implementations from USGS and others; streamflow data; NDBC buoys; satellite altimetry).
Add new visualizations or statistical analyses of the model and observational data.
We would particularly welcome suggestions for external packages (from the scientific community, like METplus, or wider python ecosystem, e.g., polars, plotly) that we can use to develop our tool without re-inventing the wheel.
Expected Outcomes
New features (1-2) that expand capabilities or improve user experience of STOFS event-based skill assessment.
I have been looking into this project and am excited about the opportunity to contribute. However, I noticed that the link to the STOFS GitHub repository is incorrect.
Project Description
This project aims to advance and improve our STOFS event dashboard (github repo). This tool allows a user to select events (e.g., tropical cyclones, winter storms, major incidents in coastal areas) and compare STOFS model results with observations for those events. The tool is currently in a prototype phase, and the mentee would have an opportunity to contribute to design, backend implementation (event definition, processing data), and frontend (data visualization). Example contributions include:
We would particularly welcome suggestions for external packages (from the scientific community, like METplus, or wider python ecosystem, e.g., polars, plotly) that we can use to develop our tool without re-inventing the wheel.
Expected Outcomes
New features (1-2) that expand capabilities or improve user experience of STOFS event-based skill assessment.
Skills Required
Python; Libraries: Xarray, Pandas, Holoviz packages. Cloud Storage.
Additional Background/Issues
No response
Mentor(s)
Jack Reeves Eyre (@JackReevesEyre-NOAA), Atieh Alipour (@AtiehAlipour-NOAA ),
Mentor Contact Email(s)
[email protected]
[email protected]
Expected Project Size
175 hours
Project Difficulty
Intermediate
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