# How to Get Support for WeatherNext: Official Channels and Best Practices

> Get help for WeatherNext by emailing weathernext@google.com, opening a GitHub issue, or exploring the Colab demo and README. Find fast support for your WeatherNext project.

- Repository: [Google DeepMind/weathernext](https://github.com/google-deepmind/weathernext)
- Tags: getting-started
- Published: 2026-08-10

---

**For WeatherNext support, contact the maintainers at `weathernext@google.com`, open a GitHub issue, or consult the Colab demo notebook and README documentation.**

WeatherNext is Google DeepMind's open-source weather forecasting system, releasing state-of-the-art models like WeatherNext 2 and WeatherNext Cyclones. Whether you're running inference on TPUs, integrating forecast data into production pipelines, or reproducing published results, knowing where to get help accelerates your progress. This guide covers every official support channel for the `google-deepmind/weathernext` repository.

## Official Contact Email for Direct Support

The fastest path for private inquiries is the dedicated maintainer email. According to [`README.md`](https://github.com/google-deepmind/weathernext/blob/main/README.md), the WeatherNext team monitors `weathernext@google.com` for questions about:

- Codebase usage and installation
- Model licensing and commercial terms
- Data access and Google Cloud integrations
- Collaboration proposals

When emailing, include your **environment details** (OS, Python version, TPU/GPU type) and **WeatherNext version** (e.g., `v0.3.0`).

## GitHub Issue Tracker for Public Discussions

For bugs, feature requests, or reproducibility questions, use the [GitHub Issues](https://github.com/google-deepmind/weathernext/issues) page. Public issues benefit the entire community and create a searchable knowledge base.

### Best Practices for Opening Issues

1. **Search existing issues first** — duplicates slow response times
2. **Use the bug report template** if available
3. **Attach a minimal reproducible example** — see the code snippet below

```python

# Minimal example to include with bug reports

import weathernext.weathernext2 as wn2

# Specify exact version used

print(wn2.__version__)

# Load model and show failure point

model = wn2.load_checkpoint(
    checkpoint_path="gs://dm_graphcast/WeatherNextCyclones_Mini_<2024.npz>"
)

```

Include the **full traceback** if an exception occurs. The maintainers reference [`weathernext/utils/checkpoint.py`](https://github.com/google-deepmind/weathernext/blob/main/weathernext/utils/checkpoint.py) for loading issues and [`weathernext/weathernext2/architecture.py`](https://github.com/google-deepmind/weathernext/blob/main/weathernext/weathernext2/architecture.py) for model-specific problems.

## Documentation and Self-Service Resources

Before contacting support, consult these authoritative sources in `google-deepmind/weathernext`:

### Interactive Tutorial

The **`docs/weathernext2/wn2_demo.ipynb`** Colab notebook provides step-by-step guidance on loading pretrained checkpoints, running autoregressive forecasts, and visualizing outputs. Open it directly from the repository or run in Google Colab for TPU access.

### Key Documentation Sections in README.md

| Section | Location | Purpose |
|---------|----------|---------|
| Installation | [`README.md`](https://github.com/google-deepmind/weathernext/blob/main/README.md#L94-L102) | `pip install` commands and dependencies |
| Data Access | [`README.md`](https://github.com/google-deepmind/weathernext/blob/main/README.md#L14-L22) | Google Cloud bucket paths and formats |
| Contact | [`README.md`](https://github.com/google-deepmind/weathernext/blob/main/README.md#L58-L60) | Official support email |

## Production Data Feeds and Cloud Support

For operational forecasting rather than research, WeatherNext offers **public data feeds on Google Cloud**. The [official developer guide](https://developers.google.com/weathernext/guides/access-forecast) covers:

- Real-time forecast access via API
- Historical reanalysis datasets
- Licensing for commercial redistribution

These feeds are maintained separately from the open-source codebase. For cloud-specific integration issues, the developer portal includes its own support channels.

## Community and Ecosystem Resources

While WeatherNext has no dedicated forum, relevant discussions occur on:

- **Stack Overflow** — Tag questions with `weathernext` or `deepmind`
- **DeepMind Blog** — Announcements of new model releases and capabilities
- **WeatherBench 2** — Related benchmarking discussions for validation datasets

## Common Support Scenarios and Code Patterns

When requesting help, demonstrating your setup with runnable code accelerates diagnosis. These patterns cover typical entry points:

### Installing a Specific Release

```bash
pip install git+https://github.com/google-deepmind/weathernext.git@v0.3.0

```

### Loading and Running a Model

```python
import weathernext.weathernext2 as wn2
import matplotlib.pyplot as plt

# Initialize from checkpoint

model = wn2.load_checkpoint(
    checkpoint_path="gs://dm_graphcast/WeatherNextCyclones_Mini_<2024.npz>"
)

# Execute 24-hour forecast (4 steps × 6 hours)

forecast = wn2.run_autoregressive(
    model=model,
    init_state=wn2.load_initial_conditions("gs://weatherbench2/ERA5_sample.zarr"),
    steps=4,
)

# Visualize surface temperature

plt.imshow(forecast["t2m"][0])
plt.title("Surface Temperature Forecast (24 h)")
plt.colorbar()
plt.show()

```

Reference [`weathernext/utils/model_utils.py`](https://github.com/google-deepmind/weathernext/blob/main/weathernext/utils/model_utils.py) for helper functions and [`weathernext/utils/checkpoint.py`](https://github.com/google-deepmind/weathernext/blob/main/weathernext/utils/checkpoint.py) if loading fails.

## What to Include in Support Requests

Speed up resolution by providing:

- **Exact error message** or traceback
- **Hardware configuration** (TPU v4/v5, GPU type, or CPU)
- **Dependency versions** (`pip list | grep -E "jax|weathernext|numpy"`)
- **Dataset location** (Cloud Storage path or local file)

## Summary

- **Email `weathernext@google.com`** for private, direct support on licensing and usage
- **Open GitHub Issues** for bugs and public discussions that benefit the community
- **Run `wn2_demo.ipynb`** for interactive, self-guided troubleshooting
- **Check [`README.md`](https://github.com/google-deepmind/weathernext/blob/main/README.md#L58-L60) and L94-L102** for authoritative contact and setup information
- **Use Google Cloud data feeds** for production-scale operational support

## Frequently Asked Questions

### Does WeatherNext have a dedicated community forum or Discord server?

No. As of the latest release, WeatherNext does not maintain an official forum or chat server. For community help, post on Stack Overflow with relevant tags, or open a GitHub Discussion if the repository enables that feature. The GitHub issue tracker remains the primary public venue.

### How quickly does the WeatherNext team respond to support emails?

Response times are not publicly specified, but the `weathernext@google.com` address is actively monitored by the DeepMind research engineering team. For time-sensitive production issues, include "[Production]" in your subject line and provide cloud project details if applicable.

### Can I get support for custom model modifications or fine-tuning?

The official channels support the released checkpoints and inference pipeline as implemented in [`weathernext/weathernext2/architecture.py`](https://github.com/google-deepmind/weathernext/blob/main/weathernext/weathernext2/architecture.py). For extended research collaborations or custom training support, email the team with a detailed proposal. The repository does not currently release training code, so fine-tuning support is limited.

### What should I do if a Google Cloud data feed is unavailable?

First verify your authentication and project billing status. If the issue persists, use the [Google Cloud support portal](https://cloud.google.com/support) for infrastructure problems, or email `weathernext@google.com` for confirmed data feed outages. Include the specific bucket path and timestamp of failed requests.