Welcome to MPASdiag Discussions!

[mrixlam]

👋 Welcome to the MPASdiag Community!

We're using Discussions as the place to connect with fellow users and developers of MPASdiag — the Python package for analyzing and visualizing MPAS (Model for Prediction Across Scales) unstructured mesh model output. Whether you're doing operational meteorology, climate model evaluation, or atmospheric research, this is your space to collaborate.

We hope that you:

• Ask questions — installation, remapping meshes to lat-lon grids, cross-sections, Skew-T diagrams, IVT/IWV diagnostics, parallel batch processing, or anything else you're wondering about.
• Share ideas — feature requests, new diagnostics, visualization improvements, or workflow enhancements.
• Show your work — publication-quality figures, case studies, or interesting analyses you've built with MPASdiag.
• Help others — answer questions, share tips, and pass on what you've learned.
• Welcome newcomers and stay open-minded — remember that this is a community we build together 💪.

To get started, comment below with a short introduction: tell us who you are, what kind of MPAS data you work with, and how you're using (or hoping to use) MPASdiag.

💡 Tip: Found a bug or have a reproducible problem? Please open an Issue instead. Use Discussions for questions, ideas, and general conversation.

[mrixlam]

📋 Discussion Best Practices — Please Read Before Posting

Welcome! To keep our community helpful and easy to navigate, here are a few dos and don'ts. Following these makes it much faster for others to help you. 🙏

✅ Do

• Pick the right category. Use Q&A for questions, Ideas for feature requests, Show and tell for sharing your work, and General for everything else.
• Search first. Someone may have already asked your question — check existing discussions before opening a new one.
• Write a clear, specific title. "IVT map is blank over the Pacific" is far better than "Help needed" or "Bug".
• Share your environment. Include your MPASdiag version, Python version, OS, and how you installed it (conda/pip).
• Provide a minimal reproducible example. Post the exact command or code snippet, your YAML config (if used), and describe the MPAS data (mesh size, variables, file structure).
• Include the full error message. Paste the complete traceback, not just the last line.
• Format code properly. Wrap commands, code, and tracebacks in triple-backtick blocks so they stay readable.
• Describe what you expected vs. what happened. And mention what you've already tried.
• Mark an answer as accepted in Q&A once your question is resolved — it helps the next person.
• Be kind and patient. Maintainers and community members help on a volunteer basis.

❌ Don't

• Don't report bugs here. Reproducible bugs and feature-blocking problems belong in Issues. Discussions are for questions, ideas, and conversation.
• Don't post screenshots of code or errors. Paste the text instead — it's searchable and easier to quote.
• Don't attach large data files. Share a small sample or a link (e.g., cloud storage) rather than full model output.
• Don't hijack existing threads with unrelated questions — start a new discussion instead.
• Don't @-mention or DM maintainers for a faster reply. Posting publicly lets anyone help and benefits others later.
• Don't post duplicates. If you find a related thread, add to it rather than opening a new one.
• Don't share sensitive information — remove credentials, private paths, or unpublished data before posting.

🚀 Quick question checklist

Before you hit "Start discussion", make sure you've included:

• A clear, descriptive title
• MPASdiag version + Python version + OS + install method
• The exact command/code you ran (in a code block)
• The full error message or unexpected output
• What you expected to happen and what you've already tried

Thanks for helping keep this a welcoming, high-signal community! 💪

[mcdev7777]

Great introduction to the MPASdiag community. The focus on diagnostics, visualization, workflows, and research use cases makes this a useful space for both users and developers to collaborate.